Windows-optimized RAG MCP Server with Playwright crawling, Link Graph trees, and local hybrid search.
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"mcp-win-stdio-rag","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# mcp-win-stdio-rag Windows-optimized RAG MCP server for indexing documentation and repositories, then retrieving cited, bounded context for coding agents. ## Tools The server exposes 10 tools: | Workflow | Tools | | --- | --- | | Indexing | `crawl_and_index_url`, `index_local_codebase`, `index_remote_repo` | | Retrieval | `query_knowledge_base`, `get_chunk_context`, `find_related_chunks`, `get_knowledge_tree` | | Collection management | `list_rag_collections`, `delete_rag_collection`, `prune_rag_cache` | ## Agent workflow 1. Index a local workspace with `index_local_codebase` or documentation with `crawl_and_index_url`; use `index_remote_repo` for GitHub sources. 2. Call `list_rag_collections` to discover available sources, then search with `query_knowledge_base`. Omit the collection to search all indexed sources. 3. Follow citations and pass both the result's `chunk_id` and `collection` to `get_chunk_context` and `find_related_chunks`; chunk IDs can repeat across collections. Use `get_knowledge_tree` to browse a collection. 4. Treat retrieval confidence as a relevance signal, not proof; confirm cited material before relying on it. ## Search and storage Search combines SQLite FTS5 BM25 with TF-IDF ranking when scikit-learn is installed, and falls back to token overlap when it is not. Confidence uses normalized whole-term overlap rather than substring matches, ignores common question filler, and abstains when fewer than one quarter of meaningful query terms are covered by the top results. Indexes are stored locally under `%USERPROFILE%\\.mcp-win-stdio\\rag_stores` by default; set `MCP_RAG_DATA_DIR` to choose another location. `prune_rag_cache` removes expired temporary collections first. Unless `purge_temp_only` is enabled, it then removes oldest-modified collections until storage is within `max_total_mb`. `delete_rag_collection` permanently removes one selected collection.
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.