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    Knowledge graph for token-efficient code reviews. Builds a structural map of your codebase with Tree-sitter, tracks changes incrementally, and gives AI agents precise context via MCP tools. Features fixed multi-word search, qualified call resolution, dual-mode embedding (ONNX local + LiteLLM cloud), and output pagination.
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    MIT
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    Self-hosted personal knowledge graph for Claude that persists across sessions, devices, and tools. Built on Neo4j with local semantic embeddings; OAuth 2.1 lets Claude Code, Claude Desktop, and claude.ai web all hit the same graph.
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    Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.
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    MIT
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    Renders source code as beautiful SVG or PNG images with syntax highlighting, line numbers, and diff support. Ideal for AI agents to present code visually to humans or for sharing snippets.
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    MCP server that exposes unified AI-friendly tools over Messari's standardized lending subgraphs on The Graph. One natural-language query → fan out across 40+ lending protocols on multiple chains → get back structured, comparable data.
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    Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.
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    MIT
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    An MCP server that enables querying Polymarket prediction market data through The Graph subgraphs. It provides tools for accessing market stats, trader P\&L, user positions, and orderbook activity using AI agents.
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    MCP server for querying AAVE V2/V3 lending protocol and governance data via The Graph subgraphs. Exposes 14 tools and 5 guided prompts that any AI agent (Claude, Cursor, Copilot, etc.) can use to query lending markets, user positions, health factors, liquidations, flash loans, rate history, and AAVE governance — across 7 chains (Ethereum, Base, Arbitrum, Polygon, Optimism, Avalanche, Fantom) via
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    An implementation of persistent memory for Claude using a local knowledge graph, allowing the AI to remember information about users across conversations with customizable storage location.
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    Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.
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    A Model Context Protocol server implementing the Random Tree Model for encoding, compressing, and recalling narrative information across different levels of abstraction with configurable cognitive parameters.
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    Persistent project memory + architectural decisions + pre-execution safety hooks for Claude Code. Local-only storage, multi-repo workspace, automatic knowledge extraction via background auditor.
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    MIT