"SQLite" matching MCP servers:

A server that exposes SQLite database operations as tools, allowing natural language interactions with a database through LlamaIndex and Ollama LLM integration.

Enables LLM agents to perform complete database operations on SQLite databases, including creating tables, executing queries, and managing data through CRUD operations with schema inspection capabilities.

Enables direct interaction with a SQLite database through custom-mapped tools for creating and retrieving items. It provides structured, AI-optimized responses and manual control over database operations without requiring external API dependencies.

Enables MCP clients to submit long-running jobs that are executed safely in isolated child processes with a durable SQLite queue, configurable timeouts, retries with backoff, and backpressure.

Bridges MCP clients with local Codex CLI to execute autonomous coding tasks, manage threads, and inspect history via SQLite state.

Enables ChatGPT on Windows to securely access codebases, Git, terminals, language servers, debuggers, SQLite, local HTTP services, adaptive project memory, engineering skills, checkpoints, audit logs, and sandboxed command execution through MCP tools.

A server that helps people access and query data in databases using the Query Runner with integration of the Model Context Protocol (MCP) Python SDK. Support databases including PostgreSQL Redshift MySQL Microsoft SQL Server Google APIs Amazon Web Services (via boto3) CockroachDB SQLite

MCP to access any database accessible via JDBC such as Postgres, Oracle, mysql, mariadb, sqlite etc.

Universal database MCP server connecting to MySQL, PostgreSQL, SQLite, DuckDB and etc.

An MCP server that keeps raw tool output out of the context window by sandboxing and compressing results (about 98% reduction), persisting file edits, git operations, tasks and decisions in SQLite with BM25 retrieval so the agent resumes after compaction, and enforcing routing across 17 platforms via MCP and hooks. It also encourages the model to write scripts that compute answers and log only results instead of reading large data into context.

Context Mode is an MCP server that reduces context window waste by sandboxing data-heavy tools, tracking session state in SQLite, and promoting code-based analysis over raw data reads, achieving up to 98% context savings.

MCP server that delegates bounded coding tasks to a server-side agent loop, persisting task state and conversations in SQLite while restricting file and command operations to a guarded workspace.

Gives an LLM a secure local workspace where it can write files, execute Python in a locked-down Docker container with no network access, and run read-only SQLite queries. Lets the model run, debug, and fix its own code without risking the host machine.