MCP server directory

This MCP (Model Context Protocol) server provides various tools to interact with dbt. You can use this MCP server to provide AI agents with context of your project in dbt Core, dbt Fusion, and dbt Platform. Read our documentation here to learn more. This blog post provides more details for what is possible with the dbt MCP server. We publish an experimental Model Context Protocol Bundle (dbt-mcp.mcpb) with each release so that MCPB-aware clients can import this server without additional setup. Download the bundle from the latest release assets and follow Anthropic's mcpb CLI docs to install or inspect it.

6 tools · generate_model_yaml, get_all_models

Cross-surface persistent memory for Claude. Bridges context between Claude Chat, Code, and Cowork via local SQLite with full-text search. Save decisions, preferences, and insights in one surface, retrieve them in any other.

Graph-structured session memory for LLMs. Local OpenAI-compatible proxy that extracts tasks, decisions, and files into a typed knowledge graph, auto-checkpoints before context overflow, and resumes any session in ~250 tokens. 6 MCP tools including `why_decision` (traces why a decision changed, with reasons and evidence). `pip install tokenmizer`

AI Summarization MCP Server, Support for multiple content types: Plain text, Web pages, PDF documents, EPUB books, HTML content

Structure any document, query it like a database. Open-source extraction engine that turns any document into typed, schema-defined records, queryable in natural language from Claude, ChatGPT, Gemini, or any MCP client.

Cloud-hosted persistent semantic memory for AI agents. Semantic search, knowledge graphs, specialist expertise hats, and multi-tenant isolation. Free 7-day trial.

Persistent memory for AI agents. Five tools (remember, recall, context, forget, share) with semantic search via vector embeddings and agent/user/org scoping. Works with Claude Code, Cursor, Windsurf, and any MCP client.

Deliberative consensus engine enabling multi-round debate between AI models with structured voting, convergence detection, and persistent decision graph memory.

Git-aware, evidence-based memory store for AI coding agents. Memories anchored to git blob hashes are automatically flagged for review when linked code changes. `pip install robo-cortex[mcp]` or on registry.modelcontextprotocol.io

Persistent memory for AI coding assistants with hybrid search (FTS5 + vector embeddings), session tracking, automatic context hooks, and web viewer. SQLite-based with no daemon process — works with Claude Code, Cursor, Windsurf, and any MCP client.

Auditable context control plane and MCP server for AI coding agents. Compresses context 70–95% (BM25 + entropy + dep-graph knapsack), stabilizes prompt prefixes for provider cache discounts, routes easy tasks to cheaper models (RAVS Bayesian router), and verifies answers locally with WITNESS hallucination guard (0.844 AUROC, $0, ~3 ms). MemoryOS adds local budget-aware working/episodic/semantic memory with decay, safety scanning, and durable persistence. 38 agent integrations (Cursor, Claude Code, Codex, Aider, and more). Ships as MCP server (`entroly serve`), HTTP proxy, or Python/Rust library. Apache-2.0, local-first. `pip install entroly`

Read and write Apple Notes with bidirectional Markdown conversion. Fast SQLite queries for listing/searching, AppleScript + native import for full CRUD. Supports stdio and Streamable HTTP transports.

📇 🏠 This is an MCP server for interacting with the VRChat API. You can retrieve information about friends, worlds, avatars, and more in VRChat.

MCP server that gives AI agents structured, ground-truth GitHub repository intelligence. Analyze tech stack, dependencies, architecture, health metrics, and security indicators with deterministic JSON output.

Production-grade persistent memory service for AI agents. Semantic search with recency decay (configurable α blend), local ONNX embeddings (zero API cost), background memory summarisation, and Prometheus/Grafana observability. `docker compose up` — no cloud dependencies.

Open-source LLM knowledge base for teams. 28-tool native MCP server turns Slack/Discord/Teams/Mattermost chat into a typed knowledge graph + auto-generated wiki with cited answers, semantic search, expert finding, and decision tracing. BYO LLM via LiteLLM, Apache 2.0, on-prem via Docker.

Validate and generate SOUL.md agent identity files from Claude Desktop. SOUL.md is the open format for persistent AI agent identity — personality, voice, values, and behavioral constraints in a machine-readable YAML file.

Production-ready RAG platform combining Graph RAG, vector search, and full-text search. Best choice for building your own Knowledge Graph and for Context Engineering

100% local semantic code search for AI agents: AST-aware chunking (tree-sitter), hybrid BM25+dense retrieval, and a code knowledge graph (callers, inheritance, imports) over codebases, docs sites, and PDFs. Install via `pipx install lynx-mcp`.

Human-like memory layer for AI agents with semantic, episodic, and procedural memory. Claude Code hooks (auto-save, auto-recall, cognitive profile). 29 MCP tools, knowledge graph, smart triggers, multi-user isolation. Python & JS SDKs.

Agent-first cognitive substrate with 18 manifest-driven verbs (germinate / eat / assimilate / sporulate / traverse / immune / molt / …) and 25 lint dimensions enforcing contract invariants mechanically (R1–R7). Cross-session / cross-project memory via a self-validating filesystem graph — AST + markdown-link derived, not embedding-based. Provider-agnostic by design: MP1/MP2 dims forbid LLM-SDK imports in the kernel and plugin tree. Editable-default install. Works with Claude Code, Cursor, Windsurf, Zed, VS Code, and any MCP client.

> One MCP server for AI agents to use tools progressively at any scale Strata is one MCP server that guides AI agents use tools reliably at any complexity, instead of overwhelming them with everything at once, it was designed by thinking human interacting with tools, solving the three major problems that plague AI agents today: Tool Overload: Too many tools cause LLM choice paralysis Context Overload: Long tool lists blow up token counts and costs Coverage Gap: Most servers are stuck at 40\~50 tools, limiting what you can build

6 tools · discover_server_categories_or_actions, execute_action

AI enhancement middleware: precise retrieval replaces full-memory loading (~80%+ token cut), rule-based conflict arbitration with explainable reasons, and one local SQLite shared across Claude Code/Codex/Cursor/ZCode. Local-first, zero cloud, MIT. `pip install memory-arbiter-mcp`

MCP server for querying 8,500+ curated awesome lists (1M+ items) and fetching the best resources for your agent.

Dual-memory MCP system (PostgreSQL 17 + pgvector + NVIDIA NIM). 11 tools: search, save, profile, health, auto-repair, stats, tune, dedup, checkpoint, maintenance. Sparse Selective Caching (SSC) with 4-phase progressive retrieval. Bilingual EN/ES. `python scripts/hipocampo_mcp_server.py`

Local index and hybrid search (SQLite FTS5 + on-device vector KNN) over your AI coding-agent conversation history across 11 tools (Claude Code, Codex, Cursor, and more). Exposes `search_threads`, `search_current_project`, `recent_threads`, and `get_thread` so any agent can recall its own past work.

Universal AI bridge for Obsidian vaults using MCP. Provides safe read/write access to notes with 11 comprehensive methods for vault operations including search, batch operations, tag management, and frontmatter handling. Works with Claude, ChatGPT, and any MCP-compatible AI assistant.

Compiles saved YouTube videos, podcasts, articles, PDFs, and Notion/Obsidian notes into a persistent, semantically searchable knowledge base any AI can query over MCP.

AI-native structured memory for coding agents — typed lore/doc entries with status and links, read and written by agents via MCP.

Distills Claude Code's 310K LoC source into 32 queryable architecture modules via MCP. 6 tools: list modules, query architecture, trace cross-cutting concerns, search patterns, and read source code. Sub-120ms p95, fully local, zero network deps.

Persistent memory for Claude Code grounded in computational neuroscience (41 cited papers). Thermodynamic decay, hippocampal-cortical consolidation, predictive-coding write gate, WRRF retrieval. PostgreSQL + pgvector, 33 MCP tools, 7 lifecycle hooks. Benchmarked 97.8% R@10 on LongMemEval. `claude plugin marketplace add cdeust/Cortex`

Shared knowledge base where AI agents exchange proven solutions — including failed approaches, so your agent skips the dead ends. Smaller models get instant access to frontier-model discoveries. Free to search indefinitely when feedback is provided on results. [Website](https://prior.cg3.io)

Local-first AI memory with causal graphs and citation verification. Semantic search, confidence decay when code drifts, and zero network connections. Works across Claude Code, Cursor, VS Code, and 7 more MCP clients.

Send push notifications to iPhone, iPad, and Mac from AI assistants. Two-way messaging — users reply in the BotBell app, AI reads and continues. Supports action buttons, Markdown, and multi-bot management via PAT.