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vedette-mcp

MCP

Enables keyword search across source-traceable evidence chunks, listing opportunities linked to supporting evidence, and deterministic ROI calculations with model-proposed inputs and TypeScript-computed dollar figures.

@meekch · v1.0.0 · MIT License · updated today

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PLUG IN

git clone https://github.com/meekch/vedette-evidence-mcp.git

See the README to configure this MCP server

README

vedette-evidence-mcp

A small MCP (Model Context Protocol) server, built to close a specific, honest gap: hands-on experience authoring an MCP server with real tools.

What it is

A working MCP server exposing three tools over stdio:

  • search_evidence — keyword search over a seeded set of evidence chunks, each traceable to a named source document.
  • list_opportunities — lists opportunities, each linked to the evidence chunk IDs that support it.
  • compute_roi — deterministic ROI math (hours saved, adoption ramp, annual dollars saved). The model may propose the inputs; every dollar figure is computed in plain TypeScript, never generated by a model. This mirrors the same model/computation separation used in Vedette.

What it is honestly

This is a demo project with seeded, fictional data (src/data.ts), built to learn and demonstrate the MCP authoring pattern: defining tools with Zod schemas, running a stdio transport, and having a client actually call them. It is not connected to a live database or a real Finance system.

Verified end to end: test-client.mjs connects a real MCP client to the built server, lists the tools, and calls all three — output captured in git history / can be re-run any time with node test-client.mjs.

Honest resume line

"Built and tested an MCP server exposing evidence search, opportunity listing, and deterministic ROI computation as callable tools, verified end-to-end with a real MCP client."

Do not claim: connection to a live production system, multi-agent orchestration (this is tool-calling by a single client, not multiple agents), or use by real users. This is a learning/demo artifact, described as exactly that.

Running it yourself

npm install
npx tsc
node test-client.mjs

Next step, if you want to extend it

Swap src/data.ts for a real Supabase query against Vedette's existing schema (evidence chunks and opportunities tables already exist there) — that would upgrade this from a demo to a real integration, and would be an honest next resume line at that point, not before.

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