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    A local Model Context Protocol server providing backend tools for AI agents to manage projects and tasks with persistent storage in SQLite, enabling structured tracking of project tasks with dependencies, priorities, and statuses.
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    GPL 3.0
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    Integrates simulated health data and task management to provide energy-aware scheduling based on calculated readiness scores. It allows users to query health summaries, manage tasks, and generate optimized daily schedules through a local SQLite database.
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    An agent-neutral MCP server providing SQLite key/value storage, Postgres knowledge base, and Kart task queue functionality. Features SAP/1.0 authorization on every tool call for secure multi-application access.
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    Apache 2.0
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    🧠 A high-performance PostgreSQL-backed MCP server acting as a super memory, task tracker, and dynamic database manager for AI agents. Features built-in connection pooling, a professional tasks schema, and a unique shared multi-agent coordination hub to prevent coding conflicts in real-time.
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    MIT
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    Enables users to manage Kanban-style tasks with priorities, tags, and statuses (todo, in progress, done) through natural language. Provides task analytics including lead time, cycle time, and status distribution with MongoDB storage.
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    Monitor and manage Apache Airflow clusters through natural language queries via MCP tools: DAG inspection, task monitoring, health checks, and cluster analytics without API complexity. * Guide: https://call518.medium.com/mcp-airflow-api-a-model-context-protocol-mcp-server-for-apache-airflow-5dfdfb2
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    MIT
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    A read-only PostgreSQL MCP server that enables AI agents to perform schema introspection and execute SELECT-only queries. It supports secure database connections through SSL and SSH tunnels while offering a structure-only mode to restrict query access.
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    MIT
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    Enables AI assistants to interact with Odoo databases via XML-RPC and JSON-RPC for performing CRUD operations and managing modules. It supports advanced features like domain-based searching, field metadata inspection, and administrative task execution.
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    MIT
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    A local MCP-style server for managing task records and seeded documents through controlled tool functions, using SQLite and JSON seed data.
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    MIT
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    Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.
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    MIT
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    Enables natural language querying of Apache Iceberg lakehouse by exposing typed tools for namespace discovery, table metadata inspection, snapshot history, time travel SQL generation, and partition pruning explanation.
    Last updated
    Apache 2.0