SQLite

The SQLite MCP server gives any AI agent direct, structured access to SQLite databases — running queries, inspecting schemas, and analyzing table contents without you having to write custom glue code for every model provider. Because SQLite databases are typically local files rather than networked services, this connector is especially useful for teams that keep operational data, prototypes, exports, or embedded application databases close to the metal instead of behind a managed database server. Ask an agent to list tables, describe column types, sample rows, or run an aggregate query, and it responds using the actual live schema rather than guessing at column names.

Inside BusinessMCP, this SQLite MCP server becomes one more data source unified under a single hosted MCP endpoint. Connect it once through your BusinessMCP dashboard and it's immediately reachable at /api/mcp using your mcph_* Bearer key — no separate server to run, no per-model integration work. Claude, GPT, Gemini, or any other MCP-compatible agent can query the same SQLite database through the identical endpoint, so switching model providers never means re-plumbing your data access layer. The business-intelligence dashboard layers reporting on top, letting non-technical stakeholders see what data agents are touching and how it's being used alongside your other connected tools, ad platforms, and revenue sources.

Typical uses lean toward local and lightweight scenarios: analyzing a SQLite export from a mobile or desktop app, running exploratory SQL over a prototype database before it graduates to Postgres or MySQL, inspecting schema drift across environments, or letting a support or ops agent answer questions against a small internal dataset without exposing raw file access. Because SQLite is file-based, it's also a natural fit for CI pipelines, developer sandboxes, and any workflow where spinning up a full database server would be overkill. When your data eventually moves to a hosted database, BusinessMCP's catalog includes matching connectors — Postgres, MySQL, MongoDB, and others — so agents keep working against the same conversational interface even as the backend evolves.

Security and compliance are handled the way the rest of BusinessMCP works: cookieless by design, GDPR-friendly, and model-agnostic, with access scoped to your Bearer key rather than embedded credentials scattered across scripts. Query and schema-inspection operations are read-oriented by default, which keeps this connector well suited for analytics and reporting use cases where you want agents reasoning over data, not mutating it unsupervised. For teams that want a single AI-agent-ready endpoint that speaks equally well to SQLite, cloud databases, marketing platforms, and everything else in their stack, this connector is a low-friction way to bring local SQL data into that same governed, hosted MCP layer alongside the BI dashboard for visibility.