toolnexus
A unified Python library that combines MCP servers, agent skills, custom functions, and HTTP endpoints into a single tool set for building AI agents with any LLM.
toolnexus
What is toolnexus?
toolnexus vs Similar AI Tools
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How to use toolnexus?
- 1Install via pip: pip install toolnexus
- 2Create a toolkit: tk = await create_toolkit()
- 3Create an agent client: agent = create_client(base_url='https://openrouter.ai/api/v1', style='openai', model='deepseek/deepseek-chat')
- 4Run an agent loop: res = await agent.run('List files here', tk)
- 5For conversations with memory, use ask(prompt, tk, id='session-1')
toolnexus Key Features
- Unified tool set from MCP servers, skills, custom functions, and HTTP endpoints
- 10 built-in tools (bash, read, write, grep, webfetch, etc.)
- Async toolkit with streaming support
- Conversation memory with pluggable store (in-memory, file, DB)
- Agent-to-Agent (A2A) communication (outbound and inbound)
- Support for multiple LLM providers (OpenAI, Anthropic, OpenRouter)
- Bring-your-own-loop with schema adapters for OpenAI/Anthropic/Gemini
- MIT open-source license
toolnexus Use Cases
- Building autonomous AI agents that can execute shell commands, read files, and access the web
- Creating tool-using chatbots with persistent memory
- Developing multi-agent systems using A2A protocol
- Rapid prototyping of LLM-powered automation workflows
- Integrating custom APIs and MCP servers as agent tools
toolnexus Pricing & Free Credits
toolnexus currently operates on a Free model.
This tool is completely free to use
toolnexus Pros & Cons
Pros
- Unified interface for diverse tool sources (MCP, skills, HTTP, custom)
- Lightweight and non-framework opinionated design
- Built-in tools enable immediate agent functionality without configuration
- Supports streaming, retries, and memory out of the box
- Multi-language ports (JS, Go, Java, C#) for cross-platform use
Cons
- Requires Python 3.11 or higher
- Dependency on MCP Python SDK may add overhead for simple use cases
- Documentation is primarily code-based; limited high-level tutorials
- A2A implementation is basic (no streaming/push/auth in v1)
What is toolnexus best for?
- Developers building AI agents with tool-use capabilities
- Teams wanting a lightweight alternative to frameworks like LangChain
- Projects needing to combine MCP servers with custom functions
- Rapid prototyping of LLM-driven automation
toolnexus FAQ
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