The financial MCP for AI agents - 90+ financial tables, SEC filings, signals, alt-data.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
One-click editor setup isnβt available for this listing yet β we donβt have a confirmed install command, and weβd rather show nothing than point your editor at the wrong package or host. Follow the projectβs own setup instructions, linked above.
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Filings, statements, earnings, ownership, events, executives, analyst data, company discovery and research signals for US, China and Japan equities β every figure traced to the document it came from.
Browser sign-in, no API key to copy. One hosted Streamable HTTP endpoint, ten tools: turn a name or a description into tickers, list and search a company's filings (structured as-reported facts and the filed text), run read-only SQL over the financial tables, and pull research signals from earnings calls and news.
β If drillr helps your agent, star us β that's how we know to keep building this in the open.
https://gateway.drillr.ai/mcp/data to an OAuth-capable MCP client as drillr-dataPer-client instructions, kept current on the docs site: https://drillr.ai/developer/mcp-install.md. Or paste this into any coding agent with a shell:
Restart, run /mcp, pick drillr-data β Authenticate.
Codex starts the browser sign-in from this command. codex mcp login drillr-data re-runs it later.
Cursor reads .cursor/mcp.json; VS Code reads .vscode/mcp.json with a top-level servers key; Claude Desktop takes the URL under Settings β Connectors β Add custom connector.
For hosts without browser OAuth (Hermes, OpenClaw, self-built clients) or for REST: create an external key at drillr.ai/account/api-keys, keep it in a secret store, and add it as a bearer header on the same URL. Never configure OAuth and a static header on the same server entry.
The companion skill teaches an agent how to onboard a user and use drillr well over REST or MCP, with a generated endpoint reference:
https://github.com/Little-Grebe-Inc/drillr-skill
"What does NVDA's latest 10-K say about supply commitments, and how did data-center revenue move over the last four quarters?"
ticker_lookup if it only has a name, filing_list to see what is indexed, then filing_search β which returns as-reported facts (value, period, XBRL concept, accession number) and the passages they sit in, in one call.run_sql on financial_statements.Each tool has a page at https://drillr.ai/docs/mcp/<tool> with parameters, limits and error shapes; the server's tools/list carries the same descriptions. The set stays small on purpose: the agent composes them.
| Group | Tool | What it does | Cost |
|---|---|---|---|
| Company | ticker_lookup | Name, brand or ticker substring β canonical symbols, historical names included | free |
company_search | Natural-language description β companies with a match reason; US / CN / JP / HK / KR; all matches returned | 3β5 cr | |
| Filings | filing_list | Which filings are indexed for a ticker: fiscal period, type, filing date | 0.1 cr |
filing_search | Search one company's filings; returns structured as-reported facts and the filing text together | 0.1 cr | |
| Datasets | list_tables | Alt-data category index, or the tables under up to five categories | free |
get_table_schema | One table's columns, types and usage note β required filters, coverage, gotchas | free | |
run_sql | One read-only PostgreSQL SELECT over the financial, market and alt-data tables | 0.1 cr | |
| Signal | industry_inflections | Industry changes synthesized from many US earnings calls: mechanism, scope, degree, per-company impact | 1 cr |
ai_adoption | Concrete enterprise AI applications disclosed on US earnings calls: workflow, stage, value, evidence | 1 cr | |
news_search | Semantic search over company and market news: storylines, events, attributed claims | 0.2 cr |
Built by drillr from primary sources β filings taken from each market's official channel (SEC EDGAR, cninfo, EDINET) and parsed in house, what companies publish on the web (IR pages, earnings calls, news), and drillr's own estimates. No data vendor in between. Every reported figure links back to the passage it was filed in. Provenance per dataset: https://drillr.ai/docs/provenance.
Factual signals from GitHub, npm, and our automated checks β not a rating.
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