microquery-mcp

<!-- mcp-name: io.github.microqueryhq/microquery-mcp -->

MCP server for Microquery — ask research questions about real-world data and get actual database records back. Works in Claude Desktop, Cursor, or any MCP-compatible AI host. Claude handles the SQL; you just ask the question.

No wallet required. Auto-registers on first query and runs on $0.10 trial credit (~1,600 typical queries).

See also

microquery-agent — autonomous agent for pipelines and cron jobs: register → deposit USDC → query → auto top-up. Use this if you want to run microquery unattended without an AI host.

Prerequisites

• Python 3.9+
• No third-party packages — stdlib only

Installation

Claude Desktop (recommended)

The easiest paths, in order of friction:

1. Registry install Find microquery in the Claude Desktop MCP marketplace or on smithery.ai and click Install. No config editing needed.

2. uvx install Add one entry to ~/Library/Application Support/Claude/claude_desktop_config.json (Mac) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "microquery": {
      "command": "uvx",
      "args": ["microquery-mcp"]
    }
  }
}

uvx requires uv to be installed separately (astral.sh/uv). Once installed, Claude Desktop will pick it up automatically.

3. Manual install (developers) Download microquery_mcp.py from this repo and point your host at it:

{
  "mcpServers": {
    "microquery": {
      "command": "python3",
      "args": ["/path/to/microquery_mcp.py"]
    }
  }
}

Restart Claude Desktop after editing. The server appears in Settings → Developer with a green dot when connected.

Other MCP hosts (Cursor, etc.)

Use the same command / args pattern above. Consult your host's MCP documentation for the exact config format.

Tools

Tool	Description
query(database, sql)	Run SQL against a microquery dataset. Auto-registers on first call.
authenticate(name, wallet_addr?)	Manually register or link a wallet address.
list_databases()	Show all available datasets and field schemas.
get_quickstart()	Sneller SQL notes and multi-dataset example recipes.

How it works

1. On the first query() call the server registers an account using your OS username (getpass.getuser()) via POST /v1/register and stores the API key in ~/.microquery/token.
2. Subsequent calls use the stored key — no configuration needed.
3. The new account starts with 100,000 µUSDC ($0.10) trial credit, covering roughly 1,600 typical queries.
4. When trial credit runs low the server automatically tops up the account (up to 10 times, $2 each). Once the free allowance is exhausted a checkout URL is returned — visit it to add USDC and continue querying.

Available datasets

FDA adverse events · SEC EDGAR · clinical trials · ClinVar · arXiv · PubMed · Ethereum · Bitcoin · Base · DeFi TVL · FEC contributions · FRED economic series · NVD/CVE · OSV advisories · sanctions · FHFA house prices · GWAS · ClinPGx · malware samples · open food facts · world bank commodities · and more — call list_databases() for the full live schema.

Example

User:    What were the top adverse events reported for metformin last year?
         And how does that compare to 2022 and 2023?
Claude:  [queries fda.faers for each year, builds trend table]
         GI events (diarrhoea, nausea, vomiting) were flat 2022→2024,
         then spiked sharply in 2025 — consistent with the longevity/
         obesity wave hitting FAERS with a lag. Lactic acidosis stayed
         nearly flat across all four years despite overall volume growth.

User:    Can you cross-reference that with genomic profiles?
Claude:  [queries clinpgx, clinvar, gwas — no SQL needed from user]
         SLC22A1 rs628031 has a direct ClinPGx annotation for GI toxicity —
         the strongest known genomic explanation for why diarrhoea and nausea
         dominate the FAERS signal for metformin.