Sourcerer – MCP for semantic code search that reduces token waste
I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files. It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions. Demo: https://asciinema.org/a/736638 GitHub: https://github.com/st3v3nmw/sourcerer-mcp
Sourcerer – MCP for semantic code search that reduces token waste launched on August 30, 2025 with 9 votes, #2,165 of 8,530 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
MCP for semantic code search & navigation that reduces token waste - st3v3nmw/sourcerer-mcp
An MCP server for semantic code search & navigation that helps AI agents work efficiently without burning through costly tokens. Instead of reading entire files, agents can search conceptually and jump directly to the specific functions, classes, and code chunks they need. go install github.com/st3v3nmw/sourcerer-mcp/cmd/sourcerer@latest Homebrew brew tap st3v3nmw/tap brew install st3v3nmw/tap/sourcerer Configuration Claude Code claude mcp add sourcerer -e OPENAI_API_KEY=your-openai-api-key -e SOURCERER_WORKSPACE_ROOT= $( pwd ) -- sourcerer mcp.json { "mcpServers" : { "sourcerer" : { "command" : " sourcerer " , "env" : { "OPENAI_API_KEY" : " your-openai-api-key " ,…from github.com
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