Collate MCP Tools Reference

Overview

This document provides detailed examples and usage patterns for all available Collate MCP tools. Each tool includes sample requests, responses, and common use cases.

Available Tools

Collate exposes 26 tools in total. Tools marked Collate-only are not available in the open-source OpenMetadata MCP Server.

Category	Type	Tools
Discover	Read	search_metadata, semantic_search, search_company_context, find_context, nlq_search ⓒ
Inspect	Read	get_entity_details, get_company_context, get_asset_context, get_persona_context, get_user_context
Knowledge	Read / Write	get_knowledge_content (Read), create_glossary, create_glossary_term, create_context_memory, create_article ⓒ (Write)
Lineage & Impact	Read / Write	get_entity_lineage, root_cause_analysis (Read), create_lineage (Write)
Govern & Classify	Write	create_classification, create_tag, create_domain, create_data_product, patch_entity
Data Quality	Read / Write	get_test_definitions (Read), create_test_case (Write)
Metrics	Write	create_metric

Paginating Large Results

Several tools return a nextCursor field in their response when more results are available. Pass that value back as the cursor (or after) parameter on the next call to fetch the next page. Tools that support pagination: search_company_context, get_test_definitions, get_persona_context (uses part). Example — paging through test definitions:

// First call
{ "name": "get_test_definitions", "arguments": { "entityType": "TABLE", "limit": 10 } }

// Response includes:
{ "nextCursor": "eyJhZnRlciI6MTB9" }

// Second call — pass the cursor as "after":
{ "name": "get_test_definitions", "arguments": { "entityType": "TABLE", "limit": 10, "after": "eyJhZnRlciI6MTB9" } }

When nextCursor is absent or null, you have reached the last page.

Discover

Search and find data assets across your catalog using keyword, semantic, or natural language queries.

search_metadata

Description: Find data assets, business terms, and data quality results in your Collate catalog. Results include a relevance score so agents can rank and filter matches by confidence. Use Cases:

Discover tables containing specific data
Find dashboards related to business areas
Search for glossary terms
Locate pipelines by name or description
Find data quality test cases and test suites

Parameters

Parameter	Type	Required	Description
`query`	string	Yes	Keywords to search for
`entityType`	string	No	Filter by entity type (table, topic, dashboard, etc.)
`size`	integer	No	Max results to return (default: 10)
`fields`	string	No	Comma-separated additional fields to include

Entity Types

Service Entities: databaseService, messagingService, apiService, dashboardService, pipelineService, storageService, mlmodelService, metadataService, searchService
Data Asset Entities: apiCollection, apiEndpoint, table, storedProcedure, database, databaseSchema, dashboard, dashboardDataModel, pipeline, chart, topic, searchIndex, mlmodel, container
User Entities: user, team
Domain Entities: domain, dataProduct
Governance Entities: metric, glossary, glossaryTerm

Examples Basic Search:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "search_metadata",
    "arguments": {
      "query": "sales"
    }
  }
}

Search for Specific Entity Type:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "search_metadata",
    "arguments": {
      "query": "customer",
      "entityType": "table",
      "size": 15
    }
  }
}

Search with Additional Fields:

{
  "jsonrpc": "2.0",
  "id": 3,
  "method": "tools/call",
  "params": {
    "name": "search_metadata",
    "arguments": {
      "query": "order",
      "entityType": "table",
      "fields": "columns,queries,upstreamLineage",
      "size": 5
    }
  }
}

Sample Response:

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "content": [
      {
        "type": "text",
        "text": "Found 5 results matching 'sales':\n\n**Tables:**\n1. **sales_transactions** (mysql_prod.ecommerce.public.sales_transactions)\n   - Description: Daily sales transaction records\n   - Service: mysql_prod (MySQL)\n   - Owners: sales-team, john.doe@company.com\n   - Tags: PII, Financial\n   - [View in OpenMetadata](https://your-om.com/table/mysql_prod.ecommerce.public.sales_transactions)\n\n2. **sales_reports** (postgresql_analytics.reporting.main.sales_reports)\n   - Description: Aggregated sales reporting data\n   - Service: postgresql_analytics (PostgreSQL)\n   - Owners: analytics-team\n   - [View in OpenMetadata](https://your-om.com/table/postgresql_analytics.reporting.main.sales_reports)\n\n**Dashboards:**\n3. **Sales Performance Dashboard** (looker_prod.sales.sales_performance)\n   - Description: Real-time sales KPI dashboard\n   - Service: looker_prod (Looker)\n   - Charts: 8 charts\n   - [View in OpenMetadata](https://your-om.com/dashboard/looker_prod.sales.sales_performance)"
      }
    ]
  }
}

semantic_search

Description: Meaning-based discovery of data assets using vector embeddings. Use this for exploratory or vague queries where exact names are unknown — it finds conceptually related assets even when keywords don’t match. Requires vector search to be enabled on your instance (supported on both OpenSearch and Elasticsearch). Parameters

Parameter	Type	Required	Description
`query`	string	Yes	Natural language description of the data you’re looking for
`filters`	object	No	Optional filters. Supported keys: `entityType` (array), `service` (array), `tags` (array)
`size`	integer	No	Number of results to return. Default is 10, maximum is 50
`k`	integer	No	Number of nearest neighbors to consider internally (KNN parameter). Default is 100
`threshold`	number	No	Minimum similarity score (0.0–1.0). Default is 0.0 (no filtering). Use `0.5`–`0.7` for high-confidence results

Examples Conceptual asset discovery:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "semantic_search",
    "arguments": {
      "query": "customer purchase history and spending behavior"
    }
  }
}

Filtered semantic search:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "semantic_search",
    "arguments": {
      "query": "revenue forecasting metrics",
      "filters": { "entityType": ["dashboard"], "service": ["BigQuery"] },
      "threshold": 0.5
    }
  }
}

search_company_context

Description: Semantic search over company context knowledge pills from the Context Center. Returns matching pills with their title, question, answer, summary, and source file. Use this to answer questions from company documents, runbooks, FAQs, and policies. Parameters

Parameter	Type	Required	Description
`query`	string	Yes	Natural-language question or topic to find relevant company knowledge for
`size`	integer	No	Number of pills to return. Default is 10, maximum is 50

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "search_company_context",
    "arguments": {
      "query": "data retention policy",
      "size": 5
    }
  }
}

find_context

Description: For a business question when no specific asset has been chosen yet — semantically searches the company knowledge layer (glossary term definitions, metric definitions, Context Center articles) and returns the relevant definitions together with candidate data assets each concept routes to. Use this before get_asset_context to identify which assets to inspect. Requires vector search to be enabled on your instance. Parameters

Parameter	Type	Required	Description
`query`	string	Yes	Natural-language question or business terms to find relevant company knowledge and candidate assets for
`size`	integer	No	Number of knowledge items to return. Default is 10, maximum is 50
`format`	string	No	Output format: `markdown` (default) or `json`

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "find_context",
    "arguments": {
      "query": "what is our definition of Monthly Active Users and where is it tracked?",
      "size": 5
    }
  }
}

nlq_search

Description: Natural language query search across data assets. Interprets free-form questions and returns matching assets from the catalog. The index parameter accepts entity type names, such as table or dashboard, or the dataAsset alias for a broad cross-entity search. Parameters

Parameter	Type	Required	Description
`query`	string	No	Natural language query. Defaults to `*` (return all)
`limit`	integer	No	Maximum number of results to return. Default is 10
`include_deleted`	boolean	No	Include deleted entities in results. Default is `false`
`index`	string	No	Entity type or index to search. Default is `dataAsset`. Accepts entity types (e.g., `table`, `testCase`) or raw index names

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "nlq_search",
    "arguments": {
      "query": "show me all Tier 1 tables in the Finance domain",
      "limit": 10
    }
  }
}

Inspect

Retrieve detailed information about specific entities and company knowledge pills.

get_entity_details

Description: Retrieve detailed information about a specific entity using its fully qualified name. The response includes custom properties defined for that entity type, in addition to standard metadata fields. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	Type of entity (table, topic, dashboard, etc.)
`fqn`	string	Yes	Fully qualified name of the entity

Examples Get Table Details:

{
  "jsonrpc": "2.0",
  "id": 4,
  "method": "tools/call",
  "params": {
    "name": "get_entity_details",
    "arguments": {
      "entityType": "table",
      "fqn": "mysql_prod.ecommerce.public.customer_orders"
    }
  }
}

Get Dashboard Details:

{
  "jsonrpc": "2.0",
  "id": 5,
  "method": "tools/call",
  "params": {
    "name": "get_entity_details",
    "arguments": {
      "entityType": "dashboard",
      "fqn": "superset_prod.sales.quarterly_revenue"
    }
  }
}

Sample Response:

{
  "jsonrpc": "2.0",
  "id": 4,
  "result": {
    "content": [
      {
        "type": "text",
        "text": "## Table: customer_orders\n\n**Fully Qualified Name**: mysql_prod.ecommerce.public.customer_orders\n\n**Basic Information**:\n- **Service**: mysql_prod (MySQL)\n- **Database**: ecommerce\n- **Schema**: public\n- **Type**: Regular Table\n- **Description**: Stores all customer order transactions with order details, timestamps, and status information\n\n**Ownership & Governance**:\n- **Owners**: ecommerce-team, sarah.johnson@company.com\n- **Tags**: PII, Financial, Customer-Data\n- **Tier**: Tier1\n\n**Schema** (5 columns):\n1. **order_id** (BIGINT) - Primary key, unique order identifier\n2. **customer_id** (BIGINT) - Foreign key to customer table\n3. **order_date** (TIMESTAMP) - When the order was placed\n4. **total_amount** (DECIMAL) - Total order value\n5. **status** (VARCHAR) - Order status (pending, completed, cancelled)\n\n**Usage Statistics**:\n- **Row Count**: ~2.5M rows\n- **Size**: 450 MB\n- **Last Updated**: 2024-01-15 09:30:00\n\n[View in OpenMetadata](https://your-om.com/table/mysql_prod.ecommerce.public.customer_orders)"
      }
    ]
  }
}

get_company_context

Description: Fetch a single company context knowledge pill by its fully qualified name. Returns the full title, question, answer, summary, and source file. Use the fullyQualifiedName or name returned by search_company_context. Parameters

Parameter	Type	Required	Description
`fqn`	string	Yes	The `fullyQualifiedName` or `name` of the knowledge pill from a `search_company_context` result. Pass it verbatim

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_company_context",
    "arguments": {
      "fqn": "data-retention-policy.gdpr-rules"
    }
  }
}

get_asset_context

Description: Get the full AI Context (Context Profile) for a single data asset in one call — the business knowledge attached to it (approved glossary term definitions, Context Center articles) plus type-specific structural context (for tables: schema, primary/foreign keys, frequently-joined columns). Use this after identifying an asset with search_metadata or find_context to gather everything needed for tasks like SQL generation without making multiple separate metadata calls. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	Type of asset (e.g., `table`, `dashboard`, `pipeline`, `topic`). Use the `entityType` value from search results
`fqn`	string	Yes	Fully qualified name of the asset. Use the exact `fullyQualifiedName` from search results
`format`	string	No	Output format: `markdown` (default, LLM-friendly) or `json`
`query`	string	No	The user’s question. When set, truncated knowledge items are expanded with the passages most relevant to this question

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_asset_context",
    "arguments": {
      "entityType": "table",
      "fqn": "mysql_prod.ecommerce.public.customer_orders",
      "query": "how is this table used in monthly revenue reports?"
    }
  }
}

get_persona_context

Description: Get the shared AI context document curated for a persona. With no personaName, uses the caller’s active persona. The document can be large and is returned in deterministic parts — call again with increasing part values while hasMore is true. Parameters

Parameter	Type	Required	Description
`personaName`	string	No	Fully qualified name of a persona. Omit to use the caller’s active persona
`format`	string	No	Output format: `markdown` (default) or `json`
`part`	integer	No	One-based document part to return. Start at `1` and continue while `hasMore` is `true`

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_persona_context",
    "arguments": {
      "part": 1
    }
  }
}

get_user_context

Description: Get context about the currently authenticated user — identity, team memberships, roles (direct and team-inherited), domains, active persona, and lightweight summaries of owned and followed entities. The tool resolves the user from the request’s auth token only — it cannot read another user’s context. Parameters

Parameter	Type	Required	Description
`includeOwnedSummary`	boolean	No	Include a summary of entities owned by the user and their teams. Defaults to `true`
`includeFollowedSummary`	boolean	No	Include a summary of entities the user follows. Defaults to `true`
`ownedLimit`	integer	No	Max owned entities to return (1–100). Defaults to 20
`followedLimit`	integer	No	Max followed entities to return (1–100). Defaults to 20
`ownedFilter`	string	No	Narrow owned entities: `NONE` (default, all owned), `MISSING_DESCRIPTION`, `MISSING_TIER`, or `ANY_GAP`

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_user_context",
    "arguments": {
      "ownedFilter": "MISSING_DESCRIPTION",
      "ownedLimit": 10
    }
  }
}

Lineage & Impact

Explore data dependencies, trace upstream sources, and analyze downstream impact.

get_entity_lineage

Description: Retrieve upstream and downstream lineage information for any entity to understand data dependencies and impact analysis. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	Type of entity
`fqn`	string	Yes	Fully qualified name of the entity
`upstreamDepth`	integer	No	Number of upstream hops to traverse (default: 3)
`downstreamDepth`	integer	No	Number of downstream hops to traverse (default: 3)
`includeColumnLineage`	boolean	No	Include column-level lineage mappings. Default is `false` (table-level only)

create_lineage

Description: Create a lineage relationship between two data assets. Requires the entity IDs (UUIDs), which get_entity_details or search_metadata can retrieve. Parameters

Parameter	Type	Required	Description
`fromEntity`	object	Yes	Source entity with `type` (entity type string) and `id` (UUID)
`toEntity`	object	Yes	Destination entity with `type` and `id`

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_lineage",
    "arguments": {
      "fromEntity": {
        "type": "table",
        "id": "a1b2c3d4-0000-0000-0000-111111111111"
      },
      "toEntity": {
        "type": "table",
        "id": "e5f6a7b8-0000-0000-0000-222222222222"
      }
    }
  }
}

root_cause_analysis

Description: Perform root cause analysis via data quality lineage. Identifies upstream failures causing issues on the specified asset, then analyzes downstream impact. If status is failed, check upstreamAnalysis for root causes and downstreamAnalysis for impact. Parameters

Parameter	Type	Required	Description
`fqn`	string	Yes	Fully qualified name of the entity to analyze
`entityType`	string	Yes	Type of the entity (e.g., `table`, `dashboard`)
`upstreamDepth`	integer	No	Number of levels upstream to traverse. Default is 3
`downstreamDepth`	integer	No	Number of levels downstream to traverse (only used when upstream failures are found). Default is 3
`includeColumnLineage`	boolean	No	Include column-level lineage on edges. Default is `false` (table-level only)
`includeDeleted`	boolean	No	Include deleted entities. Default is `false`

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "root_cause_analysis",
    "arguments": {
      "fqn": "bigquery_prod.analytics.reporting.sales_summary",
      "entityType": "table",
      "upstreamDepth": 3,
      "downstreamDepth": 3
    }
  }
}

Knowledge

Create and manage glossaries, terms, articles, and reusable context memories.

create_glossary

Description: Create a new glossary to organize business terms and definitions. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the glossary
`description`	string	Yes	Description of the glossary
`owners`	array	No	List of owners (users or teams)
`reviewers`	array	No	List of reviewers (users or teams)
`mutuallyExclusive`	boolean	Yes	Whether terms are mutually exclusive

Examples Create Business Glossary:

{
  "jsonrpc": "2.0",
  "id": 6,
  "method": "tools/call",
  "params": {
    "name": "create_glossary",
    "arguments": {
      "name": "Marketing Terms",
      "description": "Collection of marketing-related terms and definitions used across campaigns, analytics, and reporting",
      "owners": ["marketing-team", "alice.smith@company.com"],
      "reviewers": ["data-governance-team"],
      "mutuallyExclusive": false
    }
  }
}

Create Technical Glossary:

{
  "jsonrpc": "2.0",
  "id": 7,
  "method": "tools/call",
  "params": {
    "name": "create_glossary",
    "arguments": {
      "name": "Data Quality Metrics",
      "description": "Standardized definitions for data quality measurements and KPIs",
      "owners": ["data-quality-team"],
      "mutuallyExclusive": true
    }
  }
}

Sample Response:

{
  "jsonrpc": "2.0",
  "id": 6,
  "result": {
    "content": [
      {
        "type": "text",
        "text": "✅ Successfully created glossary: **Marketing Terms**\n\n**Details**:\n- **Name**: Marketing Terms\n- **Description**: Collection of marketing-related terms and definitions used across campaigns, analytics, and reporting\n- **Owners**: marketing-team, alice.smith@company.com\n- **Reviewers**: data-governance-team\n- **Mutually Exclusive**: No\n- **Status**: Active\n\n**Next Steps**:\n- You can now add glossary terms to this glossary\n- Consider creating hierarchical terms for better organization\n- Set up approval workflows if needed\n\n[View Glossary in OpenMetadata](https://your-om.com/glossary/marketing-terms)"
      }
    ]
  }
}

create_glossary_term

Description: Create a new term within an existing glossary, with support for hierarchical relationships. Parameters

Parameter	Type	Required	Description
`glossary`	string	Yes	FQN of the parent glossary
`name`	string	Yes	Name of the term
`description`	string	Yes	Definition of the term
`parentTerm`	string	No	FQN of parent term for hierarchy
`owners`	array	No	List of owners (users or teams)

Examples Create Root Level Term:

{
  "jsonrpc": "2.0",
  "id": 8,
  "method": "tools/call",
  "params": {
    "name": "create_glossary_term",
    "arguments": {
      "glossary": "marketing-terms",
      "name": "Customer Acquisition Cost",
      "description": "The total cost of acquiring a new customer, including marketing and sales expenses divided by the number of customers acquired in a specific period",
      "owners": ["marketing-team", "finance-team"]
    }
  }
}

Create Child Term:

{
  "jsonrpc": "2.0",
  "id": 9,
  "method": "tools/call",
  "params": {
    "name": "create_glossary_term",
    "arguments": {
      "glossary": "marketing-terms",
      "parentTerm": "marketing-terms.customer-acquisition-cost",
      "name": "Organic CAC",
      "description": "Customer acquisition cost specifically for customers acquired through organic channels (SEO, word of mouth, etc.) without paid advertising",
      "owners": ["marketing-team"]
    }
  }
}

Sample Response:

{
  "jsonrpc": "2.0",
  "id": 8,
  "result": {
    "content": [
      {
        "type": "text",
        "text": "✅ Successfully created glossary term: **Customer Acquisition Cost**\n\n**Details**:\n- **Glossary**: Marketing Terms\n- **Full Path**: marketing-terms.customer-acquisition-cost\n- **Definition**: The total cost of acquiring a new customer, including marketing and sales expenses divided by the number of customers acquired in a specific period\n- **Owners**: marketing-team, finance-team\n- **Status**: Draft\n\n**Suggestions**:\n- Consider adding related terms like 'Customer Lifetime Value' and 'Return on Ad Spend'\n- You might want to create child terms for different acquisition channels\n- Add synonyms if this term is known by other names in your organization\n\n[View Term in OpenMetadata](https://your-om.com/glossary/marketing-terms/customer-acquisition-cost)"
      }
    ]
  }
}

create_context_memory

Description: Save a reusable piece of knowledge to the Context Center — a preference, instruction, runbook step, or FAQ answer the assistant should retain across conversations. Use this when the user explicitly asks you to remember, note, or store something. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Stable, unique system name. Reusing an existing name updates that memory
`question`	string	Yes	The canonical question or instruction this memory represents
`answer`	string	Yes	The canonical answer or guidance to retain
`title`	string	No	Short human-readable title shown in the Context Center
`summary`	string	No	One-line summary of the memory
`memoryType`	string	No	`Preference`, `UseCase`, `Note`, `Runbook`, or `Faq`. Defaults to `Note`
`memoryScope`	string	No	`UserGlobal` (broad) or `EntityScoped` (tied to a specific entity)
`owners`	array	No	Collate usernames or team names
`tags`	array	No	Tag FQNs to apply
`domains`	array	No	Domain FQNs this memory belongs to

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_context_memory",
    "arguments": {
      "name": "finance-warehouse-preference",
      "title": "Finance Dashboard Warehouse",
      "question": "Which warehouse should finance dashboards query?",
      "answer": "Always query the FINANCE_PROD warehouse for finance dashboards.",
      "memoryType": "Preference",
      "memoryScope": "UserGlobal",
      "domains": ["Finance"]
    }
  }
}

get_knowledge_content

Description: Progressive disclosure for attached knowledge. get_asset_context and find_context return bounded excerpts of long glossary definitions, metric definitions, and Context Center articles (each marked contentTruncated). When the agent needs the full detail of one specific item, call this tool with that item’s type and fullyQualifiedName. Without a query it returns the full body; with a query it returns only the most relevant passages. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	The knowledge item type: `glossaryTerm`, `metric`, `page`, or `contextMemory`
`fqn`	string	Yes	The `fullyQualifiedName` of the knowledge item to fetch
`query`	string	No	When set, returns only the passages most relevant to this query instead of the full body
`size`	integer	No	Number of relevant passages to return when `query` is set. Default is 3, maximum is 10
`format`	string	No	Output format: `markdown` (default) or `json`

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_knowledge_content",
    "arguments": {
      "entityType": "glossaryTerm",
      "fqn": "marketing-terms.customer-acquisition-cost",
      "query": "organic vs paid acquisition"
    }
  }
}

create_article

Description: Create a new knowledge article in the Collate knowledge base. Articles can be nested under a parent page and support an approval workflow when reviewers are set. Valid entityStatus values are: Draft, In Review, Approved, Deprecated, Rejected, Unprocessed. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Unique system name for the article
`displayName`	string	No	Human-readable display name
`description`	string	No	Article content in Markdown format
`owners`	array	No	Collate usernames or team names to set as owners
`reviewers`	array	No	Collate usernames or team names to set as reviewers. When set, the article enters an approval workflow
`tags`	array	No	Tag FQNs to apply (e.g., `Tier.Tier1`)
`domains`	array	No	Domain FQNs this article belongs to
`entityStatus`	string	No	Lifecycle status: `Draft`, `In Review`, `Approved`, `Deprecated`, `Rejected`, or `Unprocessed`
`parent`	string	No	FQN of the parent knowledge page to nest this article under

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_article",
    "arguments": {
      "name": "orders-table-guide",
      "displayName": "Orders Table Guide",
      "description": "## Overview\nThe `orders` table records all customer purchase transactions...",
      "owners": ["data-platform-team"],
      "reviewers": ["data-governance-team"],
      "tags": ["Tier.Tier1"],
      "domains": ["Finance"],
      "entityStatus": "Draft"
    }
  }
}

Govern & Classify

Define and apply classifications, tags, domains, data products, and entity updates.

create_classification

Description: Create a new Classification in Collate. A Classification is a top-level container that groups related Tags, such as PII or Tier. The name becomes the root segment of every tag FQN under it. The mutuallyExclusive flag is immutable once the classification exists. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the classification. Becomes the root segment of tag FQNs (e.g., `PII` → `PII.Sensitive`). Must be unique.
`description`	string	Yes	Description of the classification in Markdown format.
`displayName`	string	No	Human-readable display name.
`mutuallyExclusive`	boolean	No	If `true`, an entity can only carry one tag from this classification at a time. Immutable after creation.
`owners`	array	No	Collate usernames or team names to set as owners. Each must already exist.
`reviewers`	array	No	Collate usernames or team names to set as reviewers. Each must already exist.
`domains`	array	No	FQNs of domains this classification belongs to. Each domain must already exist.

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_classification",
    "arguments": {
      "name": "PII",
      "description": "Tags for classifying Personally Identifiable Information across data assets.",
      "mutuallyExclusive": false,
      "owners": ["data-governance-team"],
      "reviewers": ["privacy-team"]
    }
  }
}

create_tag

Description: Create a new Tag inside an existing Classification in Collate. The tag FQN is Classification.TagName, for example PII.Sensitive. At least one of classification or parent must be provided. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the tag (the leaf segment, e.g., `Sensitive`). Must be unique within its parent.
`description`	string	Yes	Description of the tag in Markdown format.
`classification`	string	No	Name of the classification this tag belongs to (e.g., `PII`). Must already exist. Optional if `parent` is provided.
`parent`	string	No	FQN of the parent tag for a nested tag (e.g., `PII.PersonalData`). Must already exist. Omit for a top-level tag.
`displayName`	string	No	Human-readable display name.
`mutuallyExclusive`	boolean	No	If `true`, child tags under this tag are mutually exclusive on an entity.
`owners`	array	No	Collate usernames or team names to set as owners. Each must already exist.
`reviewers`	array	No	Collate usernames or team names to set as reviewers. Each must already exist.
`domains`	array	No	FQNs of domains this tag belongs to. Each domain must already exist.

Examples Create a top-level tag:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_tag",
    "arguments": {
      "name": "Sensitive",
      "description": "Data that contains sensitive personal information requiring strict access controls.",
      "classification": "PII"
    }
  }
}

Create a nested tag:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "create_tag",
    "arguments": {
      "name": "Email",
      "description": "Email addresses — a subset of sensitive personal data.",
      "parent": "PII.Sensitive"
    }
  }
}

create_domain

Description: Create a new Domain in Collate. A Domain is a top-level governance grouping of data assets. To create a child domain, set parent to the FQN of an existing parent domain. domainType defaults to Aggregate if omitted. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the domain. Must be unique.
`description`	string	Yes	Description of the domain in Markdown format.
`domainType`	string	No	Type of domain: `Source-aligned`, `Consumer-aligned`, or `Aggregate` (default).
`parent`	string	No	FQN of an existing parent domain when creating a child domain. Omit for a top-level domain.
`displayName`	string	No	Human-readable display name.
`experts`	array	No	Collate login names of domain experts (e.g., `john.doe`). Each must already exist.
`owners`	array	No	Collate usernames or team names to set as owners. Each must already exist.
`tags`	array	No	Tag FQNs to apply to this domain (e.g., `Tier.Tier1`).

Examples Create a top-level domain:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_domain",
    "arguments": {
      "name": "Finance",
      "description": "Domain for all finance and accounting data assets.",
      "domainType": "Consumer-aligned",
      "experts": ["jane.doe"],
      "owners": ["finance-team"]
    }
  }
}

Create a child domain:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "create_domain",
    "arguments": {
      "name": "Revenue",
      "description": "Sub-domain covering revenue tracking and forecasting.",
      "domainType": "Aggregate",
      "parent": "Finance"
    }
  }
}

create_data_product

Description: Create a new Data Product in Collate. A Data Product groups data assets that deliver business value and must belong to at least one Domain. All referenced domain FQNs must already exist. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the data product. Must be unique.
`description`	string	Yes	Description of the data product in Markdown format.
`domains`	array	Yes	FQNs of the domains this data product belongs to (e.g., `Finance`). At least one required; each must already exist.
`displayName`	string	No	Human-readable display name.
`experts`	array	No	Collate login names of data product experts (e.g., `john.doe`). Each must already exist.
`owners`	array	No	Collate usernames or team names to set as owners. Each must already exist.
`reviewers`	array	No	Collate usernames or team names to set as reviewers. Each must already exist.
`tags`	array	No	Tag FQNs to apply to this data product (e.g., `Tier.Tier1`, `PII.Sensitive`).

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_data_product",
    "arguments": {
      "name": "customer_360",
      "displayName": "Customer 360",
      "description": "Unified view of customer data including orders, support history, and lifetime value.",
      "domains": ["Finance", "Marketing"],
      "experts": ["alice.smith"],
      "owners": ["data-platform-team"],
      "tags": ["Tier.Tier1"]
    }
  }
}

patch_entity

Description: Update an entity using JSON Patch operations. Always look up the entity first to get its current state and UUID before patching. Array fields use plural names in paths: /domains, /owners, /tags, /reviewers. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	Type of entity to patch (e.g., `table`, `glossaryTerm`)
`fqn`	string	Yes	Fully qualified name of the entity to patch
`patch`	string	Yes	JSON Patch operations array as a JSON string. Each operation has `op` (`add`/`remove`/`replace`), `path`, and `value`

Examples Update a description:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "patch_entity",
    "arguments": {
      "entityType": "table",
      "fqn": "mysql_prod.ecommerce.public.orders",
      "patch": "[{\"op\": \"add\", \"path\": \"/description\", \"value\": \"Stores all customer orders with status and totals.\"}]"
    }
  }
}

Add a domain:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "patch_entity",
    "arguments": {
      "entityType": "table",
      "fqn": "mysql_prod.ecommerce.public.orders",
      "patch": "[{\"op\": \"add\", \"path\": \"/domains/0\", \"value\": {\"id\": \"<domain-uuid>\", \"type\": \"domain\", \"name\": \"Finance\"}}]"
    }
  }
}

Data Quality

Access test definitions and create test cases to validate your data assets.

get_test_definitions

Description: List available test definitions that can be used to create data quality test cases. Use entityType=TABLE for table-level tests and entityType=COLUMN for column-level tests. Pass results to create_test_case. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	`TABLE` for table-level tests or `COLUMN` for column-level tests
`testPlatform`	string	No	Test platform filter. Default is `OpenMetadata`. Other options: `GreatExpectations`, `DBT`, `Deequ`, `Soda`, `Other`
`limit`	integer	No	Maximum number of results to return. Default is 10
`after`	string	No	Cursor value from a previous response’s `nextCursor` field for pagination

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_test_definitions",
    "arguments": {
      "entityType": "TABLE",
      "testPlatform": "OpenMetadata",
      "limit": 10
    }
  }
}

create_test_case

Description: Create a data quality test case for a table or column. Use get_test_definitions first to find the right test definition and its required parameters. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the test case
`fqn`	string	Yes	Fully qualified name of the table to test. Always use the table FQN, not a column FQN
`testDefinitionName`	string	Yes	Name of the test definition to use
`parameterValues`	array	Yes	Array of `{ "name": "<param>", "value": "<value>" }` objects matching the test definition’s parameters
`columnName`	string	No	Column name (leaf only, e.g., `shop_id`) for column-level tests
`description`	string	No	Description of the test case

Examples Table-level row count test:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_test_case",
    "arguments": {
      "name": "orders_row_count_check",
      "fqn": "mysql_prod.ecommerce.public.orders",
      "testDefinitionName": "tableRowCountToBeBetween",
      "parameterValues": [
        { "name": "minValue", "value": "1000" },
        { "name": "maxValue", "value": "10000000" }
      ],
      "description": "Ensures the orders table always has rows within expected bounds."
    }
  }
}

Column uniqueness test:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "create_test_case",
    "arguments": {
      "name": "orders_id_uniqueness",
      "fqn": "mysql_prod.ecommerce.public.orders",
      "testDefinitionName": "columnValuesToBeUnique",
      "columnName": "order_id",
      "parameterValues": []
    }
  }
}

Metrics

Define and track measurable business and technical KPIs.

create_metric

Description: Create a new Metric entity representing a measurable business or technical KPI, such as daily revenue or error rate. Metrics can be expressed in SQL, Python, Java, or JavaScript. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Unique name for the metric. Must not contain `::`
`metricExpressionLanguage`	string	Yes	Language for the expression: `SQL`, `Java`, `JavaScript`, `Python`, or `External`
`metricExpressionCode`	string	Yes	Code or query that computes the metric (e.g., a SQL `SELECT` statement)
`description`	string	No	Description in Markdown format
`displayName`	string	No	Human-readable display name
`metricType`	string	No	`COUNT`, `SUM`, `AVERAGE`, `RATIO`, `PERCENTAGE`, `MIN`, `MAX`, `MEDIAN`, `MODE`, `STANDARD_DEVIATION`, `VARIANCE`, or `OTHER`
`granularity`	string	No	Time granularity: `SECOND`, `MINUTE`, `HOUR`, `DAY`, `WEEK`, `MONTH`, `QUARTER`, or `YEAR`
`unitOfMeasurement`	string	No	`COUNT`, `DOLLARS`, `PERCENTAGE`, `TIMESTAMP`, `SIZE`, `REQUESTS`, `EVENTS`, `TRANSACTIONS`, or `OTHER`
`owners`	array	No	Collate usernames or team names to set as owners
`tags`	array	No	Tag FQNs (e.g., `Tier.Tier1`)
`domains`	array	No	Domain FQNs this metric belongs to

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_metric",
    "arguments": {
      "name": "daily_revenue",
      "displayName": "Daily Revenue",
      "description": "Total revenue from completed orders for a given day.",
      "metricExpressionLanguage": "SQL",
      "metricExpressionCode": "SELECT SUM(total_amount) FROM orders WHERE status = 'completed' AND DATE(order_date) = CURRENT_DATE",
      "metricType": "SUM",
      "granularity": "DAY",
      "unitOfMeasurement": "DOLLARS",
      "owners": ["finance-team"],
      "tags": ["Tier.Tier1"]
    }
  }
}

​Collate MCP Tools Reference

​Overview

​Available Tools

​Paginating Large Results

​Discover

​search_metadata

​semantic_search

​search_company_context

​find_context

​nlq_search

​Inspect

​get_entity_details

​get_company_context

​get_asset_context

​get_persona_context

​get_user_context

​Lineage & Impact

​get_entity_lineage

​create_lineage

​root_cause_analysis

​Knowledge

​create_glossary

​create_glossary_term

​create_context_memory

​get_knowledge_content

​create_article

​Govern & Classify

​create_classification

​create_tag

​create_domain

​create_data_product

​patch_entity

​Data Quality

​get_test_definitions

​create_test_case

​Metrics

​create_metric

Collate MCP Tools Reference

Overview

Available Tools

Paginating Large Results

Discover

search_metadata

semantic_search

search_company_context

find_context

nlq_search

Inspect

get_entity_details

get_company_context

get_asset_context

get_persona_context

get_user_context

Lineage & Impact

get_entity_lineage

create_lineage

root_cause_analysis

Knowledge

create_glossary

create_glossary_term

create_context_memory

get_knowledge_content

create_article

Govern & Classify

create_classification

create_tag

create_domain

create_data_product

patch_entity

Data Quality

get_test_definitions

create_test_case

Metrics

create_metric