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An MCP server that provides tools for interacting with MongoDB databases, including document operations, collection management, and index management.
MongoDB MCP server has 8 tools with basic schemas and descriptions, but significant quality gaps prevent production use. All tools have descriptions (10-200 chars, baseline 194), but most are generic and lack actionable context. Input schemas are present with type definitions, but parameter descriptions are minimal (e.g., 'Filter to identify the document' for a complex MongoDB query object). No output schemas documented. Error handling returns raw exception text without recovery guidance. Tool names are clear (verb_noun pattern: createIndex, dropIndex, find, insertOne, updateOne, deleteOne, listCollections, indexes) but descriptions don't explain WHEN to use each tool or dependencies between them. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) despite clear risk levels. Composition is reasonable (8 single-purpose tools), but responses lack pagination support and field-level documentation.
Create a new index on a MongoDB collection. Args: collection: Name of the collection indexSpec: Index specification (e.g., { field: 1 } for ascending index) Returns: A dictionary with the name of the created index.
Delete a single document from a collection. Args: collection: Name of the collection filter: Filter to identify the document Returns: A dictionary with number of deleted documents.
Drop an index from a MongoDB collection. Args: collection: Name of the collection indexName: Name of the index to drop Returns: A dictionary with the drop index result.
Query documents in a collection using MongoDB query syntax. Args: collection: Name of the collection to query filter: MongoDB query filter (default {}) limit: Max number of documents to return (default 10, max 1000) projection: Fields to include/exclude (default {}) Returns: A dictionary with the query results.
List indexes for a MongoDB collection. Args: collection: Name of the collection Returns: A dictionary with the list of index definitions.
No output schemas documented. LLMs cannot predict response structure or plan downstream calls. All 8 tools return generic 'content' + 'isError' wrapper without field-level documentation.
Parameter descriptions are generic and lack constraints. 'Filter to identify the document' does not explain MongoDB query syntax, valid operators, or format. 'Index specification (e.g., { field: 1 })' includes example values that LLMs may reuse literally.
No tool annotations (readOnlyHint, destructiveHint, idempotentHint). Risk levels are declared in metadata but not in tool definitions. LLMs cannot infer which tools are safe to retry or have side effects.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 48 | <=2025-11-25 | v2 |
Insert a single document into a MongoDB collection. Args: collection: Name of the collection document: Document to insert Returns: A dictionary with insertion result.
List all available collections in the database. Returns: A dictionary containing the list of collections and their types.
Update a single document in a MongoDB collection. Args: collection: Name of the collection filter: Filter to identify document update: Update operations to apply Returns: A dictionary with the update result.
Error handling returns raw exception text without recovery guidance. 'Collection name must be a string' is actionable, but 'MongoDB connection error' or database-level errors provide no next steps for the LLM.
find() tool lacks pagination support. No limit enforcement documented (description says 'max 1000' but no min/max schema constraints). Large result sets will blow context windows.