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    Deterministic navigation maps over code AND markdown for AI agents: one MCP server, two lenses (tree-sitter TS/JS/Python + markdown). Map a whole project, read one function or one doc-section, ~99% less context. Merges codelens + docslens.
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    13
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    AGPL 3.0
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    A black-box flight recorder for RAG retrieval inside MCP agents. Logs what chunks the model saw, scores, sources, and rankings - so you can audit, replay, and diff retrieval runs after the fact.
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    MIT
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    Acts as a proxy/router for multiple downstream MCP servers, exposing only meta-tools to the host to reduce token usage, enabling efficient search and invocation of tools from a fleet of servers.
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    MIT
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    A 100% local development monitoring tool that captures browser console logs, network requests, and backend server output for analysis by AI assistants via MCP. It enables LLMs to debug applications by providing structured, real-time access to full-stack log data and persistent local storage.
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    MIT
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    Provides educational US market analysis by combining exchange rates, stock snapshots, and five famous investor perspectives (Buffett, Graham, Lynch, Dalio, Wood) to generate watchlist ideas, reasoning, risks, and follow-up checks.
    Last updated
    MIT
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    Enables AI agents to inspect and control a live Chromium browser for frontend debugging, providing console logs, network requests, DOM snapshots, and accessibility analysis.
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    MIT
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    Securely connect AI assistants to PostgreSQL databases with read-only access, schema discovery, querying, and performance analysis tools.
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    MIT
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    Provides AI agents with deep visibility into a running web page's UI by capturing DOM, styles, and screenshots through a lightweight bookmarklet. It facilitates design-to-code comparisons, accessibility audits, and automated CSS debugging directly within an IDE.
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    MIT
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    Scores MCP servers for launch-readiness across trust, tool UX, docs, observability, marketplace fit, and partner narrative, and generates partner briefs and launch path comparisons.
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    MIT
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    A deterministic buyer-choice simulator inside ChatGPT that compares merchant offers against user-supplied alternatives, explains wins/losses, and tests what-if changes.
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    MIT