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Add CockroachDB MCP Server to the list of community servers #2342

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Add CockroachDB MCP Server to the list of community servers #2342

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Adding CockroachDB MCP Server to the list of Community servers
Jul 14, 2025
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Merge branch 'main' into my-feature
amineelkouhen Jul 14, 2025
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Merge branch 'main' into my-feature
amineelkouhen Jul 16, 2025
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Merge branch 'main' into my-feature
amineelkouhen Jul 18, 2025
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1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -458,6 +458,7 @@ A growing set of community-developed and maintained servers demonstrates various
- **[Cloudinary](https://github.com/felores/cloudinary-mcp-server)** - Cloudinary Model Context Protocol Server to upload media to Cloudinary and get back the media link and details.
- **[CockroachDB](https://github.com/amineelkouhen/mcp-cockroachdb)** - MCP server enabling AI agents and LLMs to manage, monitor, and query **[CockroachDB](https://www.cockroachlabs.com/)** using natural language.
- **[CockroachDB MCP Server](https://github.com/viragtripathi/cockroachdb-mcp-server)** – Full - featured MCP implementation built with FastAPI and CockroachDB. Supports schema bootstrapping, JSONB storage, LLM-ready CLI, and optional `/debug` endpoints.
- **[Coda](https://github.com/universal-mcp/coda)** - Coda.io MCP server from **[agentr](https://agentr.dev/)** that provides support for reading and writing data to Coda docs and tables.
- **[code-assistant](https://github.com/stippi/code-assistant)** - A coding assistant MCP server that allows to explore a code-base and make changes to code. Should be used with trusted repos only (insufficient protection against prompt injections).
- **[code-context-provider-mcp](https://github.com/AB498/code-context-provider-mcp)** - MCP server that provides code context and analysis for AI assistants. Extracts directory structure and code symbols using WebAssembly Tree-sitter parsers without Native Dependencies.
- **[code-executor](https://github.com/bazinga012/mcp_code_executor)** - An MCP server that allows LLMs to execute Python code within a specified Conda environment.
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