Insightiq

InsightIQ: Economy Insight Assistant

InsightIQ is a local MCP server that gives an AI agent (Claude Code, Claude Desktop, or any other MCP client) the ability to look up real FRED (Federal Reserve Economic Data) series and their historical observations to answer economic questions.

The flow is:

1. An agent searches FRED's live series catalog (via the search_economic_series or get_economic_data tool) for series relevant to the user's question.
2. The agent fetches annual observations and units for the series it cares about.
3. The agent analyzes that data itself and answers the user's question — InsightIQ returns retrieved data only, it does not generate the explanation.

Install

Published on npm as insightiq-mcp. You'll need a free FRED API key first: get one here.

{

"mcpServers": { "insightiq": { "command": "npx", "args": ["-y", "insightiq-mcp"], "env": { "FRED_API_KEY": "your_fred_api_key_here" } } } }

Add that to your MCP client's config (a .mcp.json file for Claude Code, or Settings → Developer → Edit Config in Claude Desktop). See mcp/README.md for the full tool reference and per-client details.

Architecture

flowchart TD

agent[Agent / MCP Client] -->|Tool calls, stdio| mcp[InsightIQ MCP Server]

mcp -->|Search phrases| fredSearch[FRED series/search] fredSearch -->|Real FRED series IDs| mcp

mcp -->|Series IDs| fredApi[FRED API] fredApi -->|Annual observations and metadata| mcp

mcp -->|Raw retrieved data| agent

Everything runs as a single local process launched by the agent host. There is no database, no local catalog, no separate backend service, and no LLM call anywhere in InsightIQ itself — the only model doing any reasoning about the data is whichever LLM is driving the calling agent.

Tools

search_economic_series

Searches FRED's live series catalog. Takes queries: 1-3 concise, FRED-style keyword phrases (e.g. ["inflation", "consumer price index"]) rather than a full question — FRED's full-text search effectively requires every word in a phrase to match, so short specific phrases work far better than sentences. Returns real FRED series IDs and titles only; it never invents series IDs. Each phrase is run through a filler-word stripper before hitting FRED for exactly this reason. Optional limit (default 4) and tags/excludeTags (FRED's tag vocabulary, e.g. geography or seasonal adjustment) narrow results further.

get_series_observations

Fetches historical annual observations and units for specific FRED series IDs. Returns raw data only — no summary or explanation is generated.

get_economic_data

Convenience tool that chains the two above: searches for relevant series using searchQueries if given (falling back to the raw question otherwise), then fetches their observations. Still returns raw data only. Accepts the same limit/tags/excludeTags as search_economic_series.

list_series_tags

Given a topic phrase, returns the FRED tags that actually exist among matching series with their series counts — the discovery step for using tags/excludeTags above, since FRED's tag vocabulary usually can't be guessed reliably.

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Development

The following is only relevant if you want to modify this server or contribute to it — not needed to use it (see Install above for that).

• mcp/: the MCP server. src/tools/ are the exposed tools; src/services/ and src/clients/ hold the FRED search and data-fetch logic; evals/ has the MCP-level eval suite (tool contract + retrieval recall).

Prerequisites: Node.js 20 or newer, a FRED API key.

git clone https://github.com/ravi-p-k-1/InsightIQ.git

cd InsightIQ/mcp npm install

Create mcp/.env from mcp/.env.template:

FRED_API_KEY=your_fred_api_key_here

Run it directly to confirm it starts:

npm start

The repository root has a project-scoped .mcp.json that points Claude Code at your local checkout (picked up automatically when opened at the repository root, with your approval on first use) — useful for testing changes before publishing a new version.

Validation

GitHub Actions runs CI on pushes to main and on pull requests: installs dependencies and checks syntax, without calling FRED.

cd mcp

find src evals -name "*.js" -print0 | xargs -0 -n1 node --check

There is no separate unit-test suite — correctness and quality are verified through MCP-level evals that connect a real client to the real server in-process and drive it exactly the way an agent would. These call the live FRED API, so they're run manually rather than in CI:

cd mcp

npm run eval:contract # tool inventory, schema/error-path, happy-path checks npm run eval:retrieval # retrieval recall floor (single raw question) npm run eval:retrieval:smart # retrieval recall ceiling (curated query plans)

eval:retrieval measures the no-query-intelligence floor (45.3% on the current question set); eval:retrieval:smart replays a checked-in set of per-question search phrases/tags chosen the way a competent agent would (62.4%), without needing a live LLM call at eval time. See mcp/README.md for what each eval checks.