"Information about SQLite" matching MCP servers:

Search and discover AI agents, skills, prompts, bundles and MCP connectors from a curated catalog of 4500+ assets. Provides tools for searching, browsing categories, and accessing detailed information about each asset.

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

Provides an append-only SQLite journal for orchestrator/worker AI workflows, enabling delegation, reporting, verification, and tracking of tasks with built-in search and optional cloud sync.

Enables AI clients to programmatically build, validate, run, and test executable agent graphs as nodes and wires through local MCP tools, with SQLite storage and no cloud dependency.

Enables autonomous hierarchical multi-agent orchestration for MCP, with persistent SQLite state, real-time web monitoring, and support for mixing multiple CLI and direct API execution providers.

A transport-agnostic MCP seam for messages, context sharing, and task hand-off between humans, chat bots, and coding agents. Supports multiple backends like SQLite, Redis, Matrix, NATS, and XMPP to bridge Claude chat with Claude Code.

A server that enables AI models to access user geolocation information via EdgeOne Pages Functions through the Model Context Protocol.

Local-first MCP server that enables multiple Claude agents to coordinate through a shared message bus with SQLite persistence and real-time clock anchoring.

Enables coordinating two coding agents through a shared SQLite task pool with an explicit review workflow, allowing agents to query, claim, submit, review, and approve or reject tasks while enforcing reviewer and iteration safeguards.

Enables multiple coding agent sessions to form local squads where a commander dispatches tasks and executors report progress, ask questions, and receive correlated answers through MCP tools backed by a persistent SQLite message queue.

Reduces token consumption for AI coding agents by 50-70% through intelligent code context filtering, Git delta tracking, and local SQLite/Tree-sitter indexing.

Enables AI agents to exchange structured work items with an auditable lifecycle, supporting send, acknowledge, block, complete, and cancel operations via a shared SQLite-backed inbox.

Enables agents to pause and ask a human for a decision, then resume with the answer, via a self-hosted SQLite-backed MCP server with console or phone interfaces.

Enables Cursor agents to communicate via a shared chat room, allowing them to ask questions, share status, and warn about conflicts while collaborating on the same repo.

Local MCP server for indexing personal knowledge into SQLite with hybrid search, chunk-level citations, memory tools, and agent orchestration.

Enables read-only access to Pocket Agent's product information, public persona templates, and app catalog. No authentication required.

A SQLite-backed message queue system that enables multiple AI agents to communicate with each other via a simple HTTP interface.

Enables AI models to access user geolocation information through EdgeOne Pages Functions, allowing location-aware AI interactions.