A Model Context Protocol (MCP) server that provides code analysis capabilities using tree-sitter, designed to give AI assistants intelligent access
A Model Context Protocol (MCP) server that provides code analysis capabilities using tree-sitter, designed to give AI assistants intelligent access to codebases
The preferred_languages setting controls which language parsers are pre-loaded at server startup rather than on-demand. This provides several benefits:
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{
"mcpServers": {
"tree_sitter": {
"command": "python",
"args": [
"-m",
"mcp_server_tree_sitter.server"
]
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
Read, search and edit files inside allowed directories with the Model Context Protocol reference Filesystem server.
Retrieve version-aware library documentation and code examples with Context7 MCP, using resolve-library-id and query-docs.
<h3 align="center">One binary. Seven protocols. Zero dependencies.</h3>
Context injection for AI agents, triggered by the codebase itself
Inspect recorded agent runs, span trees, slow tools and approval logs with abhishekash’s read-only MCP Trace server.
Connect an MCP-compatible client to Google Tasks through a private server you run yourself. The server exposes compact tools for reading, searching