Contextflo MCP¶
A governed context layer for team analytics in chat. Contextflo connects your data warehouse to the AI tools your team already uses: hook up BigQuery, Snowflake, Postgres, Redshift, Databricks or ClickHouse (or upload a CSV), then ask questions of the real data and build live, auto-refreshing dashboards by chatting with Claude or ChatGPT over MCP. Table-level access control keeps agent access scoped.
Server type: Hosted (Streamable HTTP)
Endpoint: https://mcp.contextflo.com/mcp (anonymous initialize returns 401 Authentication required - live)
Auth: Contextflo account sign-in (OAuth flow; see the MCP client guides)
Sources: BigQuery, Snowflake, Postgres, Redshift, Databricks, ClickHouse, CSV upload
Access control: table-level permissions
Outputs: chat answers, live auto-refreshing dashboards
Docs: contextflo.com/docs (MCP client guides for Claude and ChatGPT)
Built by: Contextflo (contextflo.com)
Why This Matters for Operators¶
Self-serve analytics has been stuck between "give everyone a BI tool nobody logs into" and "answer every question in SQL yourself". Contextflo's MCP picks a third lane.
First, questions in chat, against real data. The agent queries the connected sources directly - "what was last week's churn by plan tier" - instead of waiting for a dashboard request to land in the data team's queue.
Second, governance is built in, not bolted on. Table-level access control means the whole team can query without handing the agent a warehouse superuser. That is the difference between a demo and something you can actually roll out.
Third, dashboards become a chat product. Per the vendor's blog, live auto-refreshing dashboards get built by chatting - no Tableau, no drag and drop - and stay connected to the sources.
Tools and Capabilities¶
Capability-level table from the vendor's docs; exact tool names require sign-in - the endpoint refuses anonymous enumeration (initialize returns a JSON-RPC 401 "Authentication required", which confirms liveness).
| Capability | Description |
|---|---|
| Ask data questions | Natural-language queries against connected warehouses and CSV uploads |
| Build dashboards | Live, auto-refreshing dashboards generated from chat, connected to the sources |
| Schema and table discovery | Work with the real table and schema names of your sources |
| Permission-scoped execution | Queries run against the table-level permissions granted to the workspace |
Verification (Aug 30, 2026)¶
- Endpoint live-verified: anonymous initialize at mcp.contextflo.com/mcp returns JSON-RPC error -32001 "Authentication required" (liveness with sign-in auth, same class as the Taskfolk and Jitsu verifications)
- Vendor docs: contextflo.com/docs carries MCP client pages for Claude and ChatGPT naming the endpoint
- mcp.so listing (Jul 9, 2026) and vendor blog confirm the product surface; GitHub org exists with 0-star repos and no public MCP repo
Notes and Caveats¶
- Hosted only: no self-host or stdio variant
- Young vendor: no public MCP repo, all public org repos are 0-star; treat as early adopter
- Sign-in required for everything past the endpoint check
- Warehouse credentials and table grants live in the Contextflo workspace - review their security model before connecting production data
Integration with CorpusIQ¶
CorpusIQ is the connector layer that lets AI assistants read the systems a business already runs on - accounting, payments, CRM, email, files and analytics - and answer with the source named. It is read-only by design: it retrieves data and never writes to, or acts in, a connected system, which is what makes it safe to point at live accounts.
This page is part of the CorpusIQ directory, the reference we maintain for the MCP server and agent-skill ecosystem. Run alongside CorpusIQ, a third-party server like this one can be combined with a company's own business data in a single answer.