MCP MongoDB Server

v1.0.0

MongoDB (Official)

MCPdatabasenosqlmcpmodel-context-protocol
75
Strong
About This MCP

Community-maintained MCP server for MongoDB database operations. Enables AI models to query, insert, update, and delete documents, manage collections, create indexes, and perform aggregations. Essential for AI-powered NoSQL database management and data analysis workflows.

Last Evaluated: November 9, 2025
Official Website

Trust Vector Analysis

Dimension Breakdown

🚀Performance & Reliability
+
query reliability

Query success rate testing

Evidence
MongoDB Driver — Built on official MongoDB drivers with stable query execution
highVerified: 2025-11-09
aggregation accuracy

Aggregation testing

Evidence
MongoDB Aggregation — Accurate aggregation pipeline execution
highVerified: 2025-11-09
large dataset handling

Scalability testing

Evidence
Implementation Review — Performance degrades with very large result sets; pagination needed
mediumVerified: 2025-11-09
connection stability

Connection stability testing

Evidence
MongoDB Connection Pooling — Stable connections with pooling and automatic reconnection
mediumVerified: 2025-11-09
error recovery

Error handling testing

Evidence
Implementation Review — Handles database errors with retry logic and error reporting
mediumVerified: 2025-11-09
🛡️Security
+
authentication security

Authentication mechanism review

Evidence
MongoDB Authentication — Supports MongoDB authentication mechanisms (SCRAM, X.509)
highVerified: 2025-11-09
connection string exposure

Credential security analysis

Evidence
MCP Security Model — Connection string with credentials stored locally; accessible to AI
highVerified: 2025-11-09
query injection risk

Injection vulnerability testing

Evidence
Security Analysis — AI can construct arbitrary queries; NoSQL injection risk if not validated
highVerified: 2025-11-09
data modification control

Operation authorization testing

Evidence
MongoDB Permissions — AI can insert, update, and delete documents within user permissions
highVerified: 2025-11-09
database drop risk

Destructive operation testing

Evidence
Implementation Review — Can drop collections and databases if permissions allow
mediumVerified: 2025-11-09
audit logging

Audit logging review

Evidence
MongoDB Audit — Auditing available in MongoDB Enterprise; limited in Community Edition
mediumVerified: 2025-11-09
🔒Privacy & Compliance
+
document data exposure

Data flow analysis

Evidence
MCP Data Flow — Query results and document data sent to LLM provider
highVerified: 2025-11-09
pii protection

PII protection assessment

Evidence
Privacy Analysis — No built-in PII detection or filtering; all queried data exposed
highVerified: 2025-11-09
field level security

Field security assessment

Evidence
MongoDB Field-Level Encryption — Supports field-level encryption but requires application-level implementation
mediumVerified: 2025-11-09
third party data sharing

Data sharing analysis

Evidence
LLM Provider Policies — Database content shared with LLM provider per their privacy policy
highVerified: 2025-11-09
query pattern exposure

Query privacy assessment

Evidence
Privacy Analysis — Query patterns may reveal data structure and business logic
mediumVerified: 2025-11-09
👁️Trust & Transparency
+
documentation quality

Documentation completeness review

Evidence
MongoDB MCP Docs — Good documentation but community-maintained with evolving coverage
mediumVerified: 2025-11-09
query visibility

Query logging assessment

Evidence
MCP Protocol — All queries logged in MCP transaction logs
highVerified: 2025-11-09
open source transparency

Source code review

Evidence
GitHub Repository — Open source community implementation
highVerified: 2025-11-09
operation coverage clarity

API documentation review

Evidence
MCP Server Documentation — Clear but incomplete documentation of supported MongoDB operations
mediumVerified: 2025-11-09
⚙️Operational Excellence
+
ease of setup

Setup complexity assessment

Evidence
Setup Documentation — Simple setup requiring MongoDB connection string
highVerified: 2025-11-09
query performance

Performance benchmarking

Evidence
MongoDB Performance — Performance depends on query complexity and indexing (typically 10-500ms)
mediumVerified: 2025-11-09
reliability

Reliability analysis

Evidence
MongoDB Stability — Built on mature MongoDB drivers with high reliability
highVerified: 2025-11-09
operation coverage

Feature coverage assessment

Evidence
MongoDB MCP Server — Covers CRUD operations, aggregations, indexing, and collection management
highVerified: 2025-11-09
community support

Community support assessment

Evidence
GitHub Community — Community-maintained with moderate activity
mediumVerified: 2025-11-09
Strengths
  • +Comprehensive MongoDB CRUD and aggregation capabilities
  • +Built on official MongoDB drivers with stable performance
  • +Excellent for NoSQL data analysis and document processing
  • +Supports complex aggregation pipelines and queries
  • +Open source community implementation
  • +Flexible schema-less data handling
Limitations
  • !Query results and document data exposed to LLM provider
  • !No built-in PII detection or sensitive data filtering
  • !Risk of NoSQL injection without proper query validation
  • !AI can modify or delete data within permission scope
  • !Connection strings with credentials accessible to AI
  • !Limited audit logging in MongoDB Community Edition
Metadata
license: MIT
supported platforms
0: All platforms with Node.js/Python
programming languages
0: TypeScript
1: Python
mcp version: 1.0
github repo: https://github.com/modelcontextprotocol/servers
api dependency: MongoDB Node.js Driver, PyMongo
authentication: MongoDB connection string (username/password)
first release: 2024-11
maintained by: Community

Use Case Ratings

code generation

Good for generating MongoDB queries and database schemas

customer support

Useful for querying customer data and support ticket analysis

content creation

Moderate applicability for content management systems using MongoDB

data analysis

Excellent for analyzing NoSQL data with aggregation pipelines

research assistant

Good for researching data patterns and document structures

legal compliance

High risk of exposing sensitive legal documents; requires strict controls

healthcare

High risk of HIPAA violations; not recommended without strong data controls

financial analysis

Moderate risk; financial data exposure concerns

education

Excellent for teaching NoSQL databases and data modeling

creative writing

Useful for managing story databases and character information