What problem does this project solve?
LLMs struggle when many similar tools are presented at once, causing tool confusion, infinite chains, and incorrect selections. The graph provides structured, task‑specific tool bundles to avoid overload.
@pratikjadhav2726
Basic information
Instead of dumping 1000+ tools into a model’s prompt and expecting it to choose wisely, the Unified MCP Tool Graph equips your LLM with structure, clarity, and relevance. It fixes tool confusion, prevents infinite loops, and enables modular, intelligent agent workflows.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"Unified-MCP-Tool-Graph": {
"command": "uv",
"args": [
"sync"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Unified MCP Tool Graph is a research-driven project that aggregates tool APIs from diverse Model Context Protocol (MCP) servers into a centralized Neo4j graph database. It serves as an intelligent infrastructure layer enabling large language models (LLMs) and agentic AI systems to dynamically retrieve the most relevant tools for a task without being overwhelmed by redundant options.
Clone the repository, install dependencies with uv sync, then start the unified gateway with uv run python start_unified_gateway.py. The gateway runs on http://localhost:8000. For full setup instructions see GETTING_STARTED.md.
LLMs struggle when many similar tools are presented at once, causing tool confusion, infinite chains, and incorrect selections. The graph provides structured, task‑specific tool bundles to avoid overload.
Neo4j is used as the graph database backend and is shown as optional in the architecture diagram, but it is central to the project’s design.
Examples are provided for A2A (Agent‑to‑Agent) and LangGraph agents. Support for Cline and IDEs is planned.
Only the 3–4 most relevant tools per query are retrieved and loaded into the agent’s context, minimizing distractions and preventing infinite loops.
Python with `uv` for dependency management. The gateway runs on port 8000; MCP servers are orchestrated dynamically. No authentication method is specified in the README.
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