SignalRank MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@SignalRank MCP search for 'llm evaluation metrics' with hybrid mode"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SignalRank MCP
MCP interface for SignalRank retrieval.
SignalRank MCP is a thin interoperability layer over SignalRank-RAG.
It exposes SignalRank retrieval to MCP-compatible clients without duplicating retrieval or ranking logic.
MCP client / host
│
▼
SignalRank MCP
│ authenticated HTTP
▼
SignalRank-RAGTool
search
Search SignalRank and return ranked evidence with provenance.
search(query, mode="dense", top_k=5)Supported retrieval modes:
bm25
dense
hybridResults preserve:
chunk_id
doc_id
text
score
rank
source_path
metadataRelated MCP server: mcp-rag-search
Install
git clone https://github.com/bksampadi/signalrank-mcp.git
cd signalrank-mcp
uv sync --extra devEnvironment
SignalRank-RAG must be running.
Set the same service token for SignalRank-RAG and SignalRank MCP:
SIGNALRANK_SERVICE_TOKEN=signalrank-local-devSignalRank-RAG also requires:
GROQ_API_KEY=<your-groq-api-key>SignalRank MCP defaults to:
SIGNALRANK_API_URL=http://127.0.0.1:8000Do not commit API keys or production service tokens.
Run
Start SignalRank-RAG:
uv run uvicorn signalrank.api.main:app --host 127.0.0.1 --port 8000Run with MCP Inspector:
uv run mcp dev src/signalrank_mcp/server.py --with-editable .Or run directly over stdio:
uv run signalrank-mcpClaude Code
Register the server:
claude mcp add --env SIGNALRANK_SERVICE_TOKEN=signalrank-local-dev --transport stdio signalrank -- uv run signalrank-mcpCheck the connection:
claude mcp get signalrankTest
uv run pytest -q
uv run ruff check .
uv run pyrightTested end-to-end with MCP Inspector and Claude Code.
License
MIT
Available Tools
1 toolsearchA
Search SignalRank and return ranked evidence without LLM synthesis.
Inputs: query (required), mode, top_k. Returns: mode, query, results
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 1 tool
Only one tool exists, so there is no risk of selecting between overlapping operations. The single 'search' tool has a clear, singular purpose.
The tool name 'search' is a clear, conventional verb, but with only one tool there is no broader verb_noun or convention pattern to evaluate. No inconsistency is present, though the naming style cannot be fully assessed.
A single search tool forms a thin but functionally valid server for ranked-evidence lookup. It is at the low end of acceptable scope and may leave agents wanting supplementary operations.
The search operation covers the core retrieval use case, but the one-tool surface offers no way to fetch evidence by ID, filter results independently, or inspect sources. Secondary workflows may therefore dead-end.
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