MCP Servers

10 open source tools compared. Sorted by stars. Scroll down for our analysis.

Tool	Stars	Velocity	Language	License	Score
AWS MCP Servers9 servers
documentdb-mcp-serverMCP An AWS Labs Model Context Protocol (MCP) server for AWS DocumentDB that enables AI assistants to interact with DocumentDB databases.	8.8k	-		-	53
mysql-mcp-serverMCP An AWS Labs Model Context Protocol (MCP) server for Aurora MySQL	8.8k	-		-	53
s3-tables-mcp-serverMCP > ## ⚠️ IMPORTANT: YOU ARE RESPONSIBLE FOR YOUR AGENTS	8.8k	-		-	53

mcp-mongo-serverMCP A Model Context Protocol Server for MongoDB	277	-	TypeScript	-	34

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Our Analysis

documentdb-mcp-server8.8k★

Connects your AI assistant to Amazon DocumentDB, the MongoDB-compatible document database. You can query collections, inspect indexes, run aggregation pipelines, and browse your data model without switching to a MongoDB client. The MCP server is free and open source. DocumentDB instances start around $0.08/hour for the smallest size. The server needs a connection string to your DocumentDB cluster, which typically requires VPC access or a bastion host, adding setup complexity. Maintained by AWS Labs. If you're running DocumentDB and want to explore or debug your data from your editor, this works well. The VPC networking requirement means setup is not as quick as other MCP servers in this collection.

mysql-mcp-server8.8k★

MySQL MCP connects your AI assistant to Aurora MySQL databases. Run queries, inspect schemas, and explore data without leaving your editor. Point it at your connection string and you are set. Aurora MySQL pricing is usage-based. The MCP adds zero cost. Maintained by AWS Labs with read-only defaults for safety. Solid for schema exploration and quick queries during development. The catch: it is tuned for Aurora MySQL specifically. Vanilla MySQL works but is not the primary target, so some Aurora-specific features may not translate.

s3-tables-mcp-server8.8k★

S3 Tables MCP gives your AI assistant access to S3 Tables, Amazon's Apache Iceberg table format built on S3. Query structured data stored as Iceberg tables without spinning up a separate compute engine. Setup requires AWS credentials and existing S3 Tables. S3 Tables bills on storage and requests. The MCP is free. AWS Labs maintains it as part of their analytics MCP suite. Useful for teams with data lakehouse architectures who want quick Iceberg queries from their editor. The catch: S3 Tables is still relatively new. The ecosystem is smaller than Athena or Redshift, so expect rougher edges.

amazon-sns-sqs-mcp-server8.8k★

Connects your AI assistant to AWS SNS topics and SQS queues. The model can publish messages, manage subscriptions, send and receive queue messages, and inspect queue state. Useful for AI-driven event orchestration and message debugging. You get full SNS/SQS management: topic and queue CRUD, message publishing, subscription handling, and queue polling. Requires AWS credentials. The MCP server is free, SNS/SQS pricing is usage-based and extremely cheap for normal volumes. Maintained by AWS Labs. If you debug message flows or manage event-driven architectures on AWS, this gives your AI direct access to the plumbing. Practical for ops-heavy workflows.

aurora-dsql-mcp-server8.8k★

Connects your AI assistant to Aurora DSQL, Amazon's distributed SQL database. The model can run queries, inspect schemas, and explore data across a globally distributed relational database. You get SQL query execution and schema inspection against Aurora DSQL clusters. Requires AWS credentials and a running DSQL cluster. The MCP server is free, Aurora DSQL pricing is based on compute and I/O usage. Maintained by AWS Labs. Aurora DSQL is still relatively new, so this server is early-stage but functional. If you are building on DSQL and want AI-assisted database work, it is currently the only option. Worth installing for DSQL users.

timestream-for-influxdb-mcp-server8.8k★

Timestream InfluxDB MCP connects your AI assistant to Amazon Timestream for InfluxDB, AWS's managed time-series database. Query metrics, inspect databases, and explore time-series data. Config is your InfluxDB endpoint plus AWS credentials. Timestream for InfluxDB bills on instance size and storage. The MCP is free. AWS Labs maintains it. Good fit for IoT or monitoring teams already on this service. The catch: Timestream for InfluxDB is a niche AWS offering. If you are using standalone InfluxDB or Prometheus, this is not the right connector.

dynamodb-mcp-server8.8k★

Connects your AI assistant to Amazon DynamoDB. You can scan and query tables, inspect items, check table metrics, and explore your data model. Particularly useful for understanding partition key patterns and debugging query performance. The MCP server is free and open source. DynamoDB charges per read/write capacity unit, with a free tier of 25 RCU/WCU. The MCP server's read operations cost almost nothing at normal debugging volumes. Setup is standard AWS credentials. Maintained by AWS Labs. Strong pick for any team running DynamoDB. Describing the data you want in natural language instead of crafting KeyConditionExpressions is a genuine quality-of-life improvement. Low setup cost, high daily utility.

postgres-mcp-server8.8k★

Postgres MCP connects your AI assistant to Aurora PostgreSQL databases. Run queries, inspect schemas, list tables. Setup is a connection string in your MCP config. Aurora Postgres pricing is usage-based. The MCP is free. AWS Labs maintains it with read-only query defaults. Essential if you are doing any development against Aurora Postgres. Having your AI understand your schema changes the conversation entirely. The catch: optimized for Aurora Postgres, not vanilla PostgreSQL. It works with standard Postgres, but Aurora-specific tooling is the focus.

amazon-neptune-mcp-server8.8k★

Connects your AI assistant to Amazon Neptune graph databases. The model can inspect schema, check cluster status, and run openCypher or Gremlin queries against your graph data. Graph databases are notoriously hard to query by hand, so letting AI help is a genuine productivity win. You get schema inspection, status monitoring, and query execution. Requires AWS credentials and a running Neptune cluster. The MCP server is free, but Neptune pricing starts around $0.10/hour for the smallest instance. Maintained by AWS Labs, the official open source arm of AWS. If you run Neptune and want AI-assisted graph exploration, this is the only game in town. Solid choice for existing Neptune users.

mcp-mongo-server277★

This MCP server connects your AI assistant to MongoDB. Run queries, inspect collections, check indexes, and explore your data without switching to Compass or the shell. Point it at a connection string and go. Community-maintained. Setup requires your MongoDB connection string in the config. Works with local instances, Atlas, and self-hosted deployments. No additional API keys beyond your existing database credentials. Install this if MongoDB is your primary database and you want your assistant to query it directly. Saves time on ad-hoc data exploration and debugging. The catch: community project with a single maintainer. Write operations exist, so be careful with permissions on production databases.