TeamADAPT
A protocol for seamless integration between LLM applications and external data sources
Documentation |Specification |Discussions
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.
- 📚 Read theDocumentation for guides and tutorials
- 🔍 Review theSpecification for protocol details
- 💻 Use our SDKs to start building:
- specification - Protocol specification and documentation
- typescript-sdk - TypeScript implementation
- python-sdk - Python implementation
- java-sdk - Java implementation
- kotlin-sdk - Kotlin implementation
- csharp-sdk - C# implementation
- docs - User documentation and guides
- create-kotlin-server - Kotlin sample server
- servers - List of maintained servers
We welcome contributions of all kinds! Whether you want to fix bugs, improve documentation, or propose new features, please see ourcontributing guide to get started.
Have questions? Join the discussion in ourcommunity forum.
The Model Context Protocol is an open source project run byAnthropic, PBC. and open to contributions from the entire community.
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TeamADAPT/langgraph’s past year of commit activity - langchainjs Public Forked fromlangchain-ai/langchainjs
🦜🔗 Build context-aware reasoning applications 🦜🔗
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Deepagents is an agent harness built on langchain and langgraph. Deep agents are equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - making them well-equipped to handle complex agentic tasks.
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