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"Hybrid Memory Models Combining Relational, Graph, and RAG Approaches" matching MCP servers:

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    Classifies development task complexity (LIGHT/MEDIUM/HEAVY) and recommends the most cost-efficient AI model per provider, enabling optimized model selection for coding tasks.
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    MIT
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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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    MIT
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    MCP server for querying Lido liquid staking protocol data via The Graph's decentralized network, providing tools for staking stats, APR, withdrawals, node operators, and governance.
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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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    6
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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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    MIT
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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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    MIT
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    Persistent project memory for AI models and coding agents. Memory MCP stores architecture, decisions, tasks, warnings, preferences, and session state in Supabase so OpenCode, Claude Code CLI, Qwen Code, Codex, or any MCP-compatible client can resume work without losing context.
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    1
    MIT
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    Exposes Azure Entra ID user and license management as MCP tools over HTTP-SSE, enabling operations such as user creation, group assignment, and license management via Microsoft Graph API.
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    Apache 2.0
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    Provides access to 529,000+ US statute sections across all 50 states and federal codes for comprehensive legal research. Supports semantic search, citation graph traversal, jurisdictional comparisons, and regulatory risk analysis through natural language queries.
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    MIT
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    Provides comprehensive AI model metadata through MCP, enabling search and filtering of 100+ AI models by capabilities, pricing, context length, and provider specifications.
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    MIT
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    Helps construct and validate Microsoft Graph REST API calls with on-demand tool loading, providing request details, required permissions, and code examples for categories like users, files, mail, calendar, groups, notes, tasks, sites, and subscriptions.
    Last updated
    15
    MIT
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    A self-organizing, persistent semantic memory layer that enables AI agents to store, categorize, and retrieve information using hybrid vector and keyword search. It features autonomous chunking, deduplication, and hierarchical taxonomy management through a PostgreSQL-backed MCP server.
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    MIT
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    Implements Retrieval-Augmented Generation (RAG) using GroundX and OpenAI, allowing users to ingest documents and perform semantic searches with advanced context handling through Modern Context Processing (MCP).
    Last updated
    5