OpenMetadata MCP Tools Reference

All OpenMetadata MCP tools, with parameters and examples.

Available Tools

Category	Tools
Discover	search_metadata, semantic_search
Inspect	get_entity_details
Lineage & Impact	get_entity_lineage, create_lineage, root_cause_analysis
Knowledge	create_glossary, create_glossary_term
Govern & Classify	create_classification, create_tag, create_domain, create_data_product, patch_entity
Data Quality	get_test_definitions, create_test_case
Metrics	create_metric

Which Tool to Call First

If you already have a fully qualified name, start with get_entity_details directly. If you don’t, start with search_metadata or semantic_search first, then pass the fullyQualifiedName from a result into get_entity_details. Starting broad with search_metadata when you already know the FQN adds unnecessary round trips (re-searching, re-confirming the match) that calling the lookup tool directly avoids.

Fully Qualified Name (FQN) Format

An entity’s FQN is a dot-separated path built from the entity and its ancestors. The number of segments depends on entity type:

Entity Type	FQN Pattern	Example
Table	`service.database.schema.table`	`snowflake_prod.analytics.public.customers`
Database Schema	`service.database.schema`	`snowflake_prod.analytics.public`
Database	`service.database`	`snowflake_prod.analytics`
Dashboard	`service.dashboardName`	`sample_superset.10`
Tag	`Classification.TagName`	`PII.Sensitive`
Glossary Term	`glossary.term`	`marketing-terms.customer-acquisition-cost`

Consult the entity’s API Reference page for entity types not listed here. Special Characters: If a name segment contains a period (.) or a double quote ("), wrap that segment in double quotes, escaping any internal " by doubling it. For example, a schema literally named sales.eu inside database prod becomes service.prod."sales.eu".table.

Discover

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

search_metadata

Description: Find data assets and business terms by keyword. Use when you know specific names, owners, tags, tiers, services, or column names. Use Cases:

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

Parameters

Parameter	Type	Required	Description
`query`	string	No	Keywords to search for
`entityType`	string	No	Filter by entity type (see list below)
`size`	integer	No	Max results to return (default: 10, max: 50)
`from`	integer	No	Offset for pagination (default: 0)
`fields`	string	No	Comma-separated additional fields to include
`queryFilter`	string	No	Advanced: direct OpenSearch DSL JSON query. Example: `{"bool": {"must": [{"term": {"entityType": "table"}}, {"term": {"tags.tagFQN": "PII.Sensitive"}}]}}`
`includeDeleted`	boolean	No	Include deleted entities (default: false)
`includeAggregations`	boolean	No	Include aggregation/facet data (default: false)
`maxAggregationBuckets`	integer	No	Max buckets per aggregation (default: 10, max: 50)

Omit queryFilter entirely rather than sending an empty string, "null", or "{}". A degenerate value is not treated as “no filter”: it currently produces a 400 JSON parsing failed error instead of falling through to a normal keyword search.

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 a 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\n2. **sales_reports** (postgresql_analytics.reporting.main.sales_reports)\n   - Description: Aggregated sales reporting data\n   - Service: postgresql_analytics (PostgreSQL)\n\n**Dashboards:**\n3. **Sales Performance Dashboard** (looker_prod.sales.sales_performance)\n   - Description: Real-time sales KPI dashboard\n   - Charts: 8 charts"
      }
    ]
  }
}

semantic_search

Description: Find data assets by meaning using vector search (setup guide). Use for exploratory queries where you don’t know exact names. Returns conceptually related assets even when no keywords match. Use Cases:

Explore data when you don’t know exact table names
Find assets related to a concept (e.g., “customer spending behavior”)
Discover hidden relationships across services

Parameters

Parameter	Type	Required	Description
`query`	string	Yes	Natural language description of what you’re looking for
`filters`	object	No	Optional filters: `entityType`, `service`, `tags` (each an array of strings)
`size`	integer	No	Number of results to return (default: 10, max: 50)
`k`	integer	No	KNN neighbor count for tuning result quality (default: 100)
`threshold`	number	No	Minimum similarity score 0.0–1.0 (default: 0.0)

Examples Conceptual Search:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "semantic_search",
    "arguments": {
      "query": "tables tracking customer purchase history and lifetime value"
    }
  }
}

Search with Filters and Threshold:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "semantic_search",
    "arguments": {
      "query": "revenue forecasting and financial reporting",
      "filters": {
        "entityType": ["table", "dashboard"],
        "service": ["BigQuery"]
      },
      "threshold": 0.5,
      "size": 5
    }
  }
}

Inspect

Retrieve detailed information about specific entities and company knowledge pills.

get_entity_details

Description: Retrieve full details for a specific entity by fully qualified name (FQN). If you already have the exact FQN (from a prior search result, or built from known segments using the documented FQN format), pass it directly. If you’re not certain of the exact segment values (service, database, schema, or table names as stored in OpenMetadata may differ from source-system names), use search_metadata or semantic_search first and pass through the fullyQualifiedName from the result to avoid a failed lookup. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	Type of entity (e.g., `table`, `dashboard`, `topic`, `pipeline`)
`fqn`	string	Yes	Fully qualified name — use the exact value from `search_metadata` or `semantic_search` results

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**FQN**: mysql_prod.ecommerce.public.customer_orders\n**Service**: mysql_prod (MySQL)\n**Database**: ecommerce | **Schema**: public\n**Description**: Stores all customer order transactions\n\n**Owners**: ecommerce-team, sarah.johnson@company.com\n**Tags**: PII, Financial, Customer-Data | **Tier**: Tier1\n\n**Columns** (5):\n- order_id (BIGINT) - Primary key\n- customer_id (BIGINT) - FK to customer table\n- order_date (TIMESTAMP)\n- total_amount (DECIMAL)\n- status (VARCHAR)"
      }
    ]
  }
}

Lineage & Impact

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

get_entity_lineage

Description: Retrieve upstream and downstream lineage for any entity to understand data dependencies and perform impact analysis. Pass the exact fullyQualifiedName from search results. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	Type of entity
`fqn`	string	Yes	Fully qualified name of the entity
`upstreamDepth`	integer	No	Hops to traverse upstream (default: 3, max: 10)
`downstreamDepth`	integer	No	Hops to traverse downstream (default: 3, max: 10)
`includeColumnLineage`	boolean	No	Include column-level lineage mappings. Default is `false` (table-level only)

Examples Get Full Lineage:

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_entity_lineage",
    "arguments": {
      "entityType": "table",
      "fqn": "mysql_prod.ecommerce.public.sales_transactions",
      "upstreamDepth": 3,
      "downstreamDepth": 3
    }
  }
}

Downstream-Focused Impact Analysis:

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "get_entity_lineage",
    "arguments": {
      "entityType": "table",
      "fqn": "mysql_prod.ecommerce.public.sales_transactions",
      "upstreamDepth": 1,
      "downstreamDepth": 5
    }
  }
}

create_lineage

Description: Create a lineage relationship between two entities. Requires the id (UUID) and type of both the source and destination entities. Parameters

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

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "create_lineage",
    "arguments": {
      "fromEntity": {
        "type": "table",
        "id": "3a1b2c3d-4e5f-6789-abcd-ef0123456789"
      },
      "toEntity": {
        "type": "table",
        "id": "9f8e7d6c-5b4a-3210-fedc-ba9876543210"
      }
    }
  }
}

Tip: Retrieve entity UUIDs from get_entity_details results before calling create_lineage.

root_cause_analysis

Description: Trace a data quality failure back to its origin by traversing data quality lineage across pipeline hops. Parameters

Parameter	Type	Required	Description
`fqn`	string	Yes	FQN of the entity where failure was detected
`entityType`	string	Yes	Entity type to analyze (for example, `table`)
`upstreamDepth`	integer	No	Hops to traverse upstream (default: 3, max: 10)
`downstreamDepth`	integer	No	Hops to traverse downstream (default: 3, max: 10)
`queryFilter`	string	No	Optional OpenSearch DSL filter JSON
`includeDeleted`	boolean	No	Include deleted entities in traversal (default: false)

Example

{
  "jsonrpc": "2.0",
  "id": 12,
  "method": "tools/call",
  "params": {
    "name": "root_cause_analysis",
    "arguments": {
      "fqn": "mysql_prod.ecommerce.public.customer_orders",
      "entityType": "table",
      "upstreamDepth": 4,
      "downstreamDepth": 1,
      "includeDeleted": false
    }
  }
}

Knowledge

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

create_glossary

Description: Create a new glossary to organize business terms. Set mutuallyExclusive: true to restrict entities to a single term from the glossary at a time. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the glossary
`description`	string	Yes	Description of the glossary’s purpose
`mutuallyExclusive`	boolean	Yes	If `true`, only one term from this glossary can tag an entity at a time
`owners`	array	No	List of owner usernames or emails
`reviewers`	array	No	List of reviewer usernames or emails

Examples Create a Business Glossary:

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

Create a Mutually Exclusive 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- Owners: marketing-team, alice.smith@company.com\n- Reviewers: data-governance-team\n- Mutually Exclusive: No\n- Status: Active"
      }
    ]
  }
}

create_glossary_term

Description: Create a new term within an existing glossary. Supports hierarchical parent–child relationships between terms. 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 the parent term (for nested/hierarchical terms)
`owners`	array	No	List of owner usernames or emails
`reviewers`	array	No	List of reviewer usernames or emails

Examples Create a 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 a 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 for customers acquired through organic channels (SEO, word of mouth) without paid advertising",
      "owners": ["marketing-team"]
    }
  }
}

Govern & Classify

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

create_classification

Description: Create a new Classification in OpenMetadata. A Classification is a top-level container that groups related Tags (e.g., PII, 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	OpenMetadata usernames or team names to set as owners. Each must already exist.
`reviewers`	array	No	OpenMetadata 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 a Classification in OpenMetadata. The tag FQN is Classification.TagName (e.g., 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	OpenMetadata usernames or team names to set as owners. Each must already exist.
`reviewers`	array	No	OpenMetadata 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 OpenMetadata. 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	OpenMetadata login names of domain experts (e.g., `john.doe`). Each must already exist.
`owners`	array	No	OpenMetadata 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 OpenMetadata. 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	OpenMetadata login names of data product experts (e.g., `john.doe`). Each must already exist.
`owners`	array	No	OpenMetadata usernames or team names to set as owners. Each must already exist.
`reviewers`	array	No	OpenMetadata 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 existing entity’s properties using JSON Patch (RFC 6902). Use get_entity_details first to retrieve the current state before constructing a patch. 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`

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "patch_entity",
    "arguments": {
      "entityType": "table",
      "fqn": "mysql_prod.ecommerce.public.customer_orders",
      "patch": "[{\"op\":\"replace\",\"path\":\"/description\",\"value\":\"Updated description for customer orders table.\"}]"
    }
  }
}

Data Quality

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

get_test_definitions

Description: List test definitions available in OpenMetadata for tables or columns. Call this before create_test_case to identify valid test types and their required parameters. Parameters

Parameter	Type	Required	Description
`entityType`	string	Yes	`TABLE` for table-level tests or `COLUMN` for column-level tests
`limit`	integer	No	Max results to return (default: 10)
`after`	string	No	Pagination cursor — use `nextCursor` from the previous response
`testPlatform`	string	No	Filter by platform: `OpenMetadata`, `GreatExpectations`, `DBT`, `Deequ`, `Soda`, `Other` (default: `OpenMetadata`)

Example

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_test_definitions",
    "arguments": {
      "entityType": "COLUMN",
      "limit": 20
    }
  }
}

create_test_case

Description: Create a data quality test case for a table or column. For column tests, ensure the column’s data type is listed in the test definition’s supportedDataTypes. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the test case
`fqn`	string	Yes	FQN of the target entity (typically the table FQN)
`testDefinitionName`	string	Yes	Name of the test definition returned by `get_test_definitions`
`parameterValues`	array	Yes	List of test parameter objects (`name` + `value`) required by the test definition
`columnName`	string	No	Column name for column-level test cases
`entityType`	string	No	Target OpenMetadata entity type (default: `table`). For column-level tests, keep `entityType` as `table` and set `columnName`.
`description`	string	No	Optional description of the test case

Example

{
  "jsonrpc": "2.0",
  "id": 11,
  "method": "tools/call",
  "params": {
    "name": "create_test_case",
    "arguments": {
      "name": "customer_id_not_null",
      "fqn": "mysql_prod.ecommerce.public.customer_orders",
      "columnName": "customer_id",
      "entityType": "table",
      "testDefinitionName": "columnValuesToBeNotNull",
      "description": "Ensures customer_id is always populated for downstream joins",
      "parameterValues": []
    }
  }
}

Metrics

Define and track measurable business and technical KPIs.

create_metric

Description: Create a new metric entity in OpenMetadata to track and standardize business KPIs. Parameters

Parameter	Type	Required	Description
`name`	string	Yes	Name of the metric
`description`	string	No	Description of the metric in Markdown format
`displayName`	string	No	Human-readable display name for the metric
`metricExpressionLanguage`	string	Yes	Expression language used for the metric (for example, `SQL`)
`metricExpressionCode`	string	Yes	Metric formula/expression in the selected language
`metricType`	string	No	Metric type such as `COUNT`, `SUM`, `AVERAGE`, `RATIO`, or `OTHER`
`granularity`	string	No	Time granularity such as `DAY`, `WEEK`, `MONTH`, `QUARTER`, or `YEAR`
`unitOfMeasurement`	string	No	Unit of measurement such as `COUNT`, `DOLLARS`, `PERCENTAGE`, or `OTHER`
`customUnitOfMeasurement`	string	No	Custom unit string, required when `unitOfMeasurement` is `OTHER`
`owners`	array	No	List of owner usernames or emails
`reviewers`	array	No	List of reviewer usernames or emails
`relatedMetrics`	array	No	List of related metric FQNs
`tags`	array	No	List of tags to apply
`domains`	array	No	List of domains to associate

Example

{
  "jsonrpc": "2.0",
  "id": 10,
  "method": "tools/call",
  "params": {
    "name": "create_metric",
    "arguments": {
      "name": "monthly_recurring_revenue",
      "displayName": "Monthly Recurring Revenue",
      "description": "Monthly recurring revenue from active subscriptions.",
      "metricExpressionLanguage": "SQL",
      "metricExpressionCode": "SUM(subscription_amount)",
      "metricType": "SUM",
      "granularity": "MONTH",
      "unitOfMeasurement": "DOLLARS",
      "owners": ["finance-team"],
      "reviewers": ["data-governance-team"],
      "tags": ["Finance", "KPI"],
      "domains": ["Revenue"]
    }
  }
}

​OpenMetadata MCP Tools Reference

​Available Tools

​Which Tool to Call First

​Fully Qualified Name (FQN) Format

​Discover

​search_metadata

​semantic_search

​Inspect

​get_entity_details

​Lineage & Impact

​get_entity_lineage

​create_lineage

​root_cause_analysis

​Knowledge

​create_glossary

​create_glossary_term

​Govern & Classify

​create_classification

​create_tag

​create_domain

​create_data_product

​patch_entity

​Data Quality

​get_test_definitions

​create_test_case

​Metrics

​create_metric

OpenMetadata MCP Tools Reference

Available Tools

Which Tool to Call First

Fully Qualified Name (FQN) Format

Discover

search_metadata

semantic_search

Inspect

get_entity_details

Lineage & Impact

get_entity_lineage

create_lineage

root_cause_analysis

Knowledge

create_glossary

create_glossary_term

Govern & Classify

create_classification

create_tag

create_domain

create_data_product

patch_entity

Data Quality

get_test_definitions

create_test_case

Metrics

create_metric