Yggdrasil

One shared, durable memory for all your AI coding agents — local-first, MCP, zero-dependency. Decisions, lessons, and project status persist across sessions, tools, and projects.

Model Context Protocol (MCP) server for SociaVault — query TikTok, Instagram, YouTube, Twitter/X, LinkedIn, Facebook, Reddit, Threads, Pinterest, Twitch, TikTok Shop, and ad libraries from any AI assistant.

Read-only database access with schema inspection

Agent-native search engine with live web research optimized for AI agents.

Browser automation and web scraping

The Milvus MCP server enables AI applications to interact with Milvus vector databases using natural language commands. It allows AI models to perform vector searches, manage collections, and retrieve data without writing custom database queries. This integration facilitates seamless access to vector data, enhancing the capabilities of AI tools like Claude Desktop and Cursor.

Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.

An MCP server implementation for retrieving information from the AWS Knowledge Base using the Bedrock Agent Runtime.

Stop hallucinating numbers. An MCP server that runs every math expression through four independent numeric engines in parallel and returns all four results side by side — so when they disagree, you know the answer is numerically unreliable.

An MCP server that provides a tool for sending transactional emails via Mailtrap

Shop across every brand store on Tolstoy in chat — marketplace-wide product search, full product details, and virtual try-on. Public, no sign-in.

Intelligent repository context for AI coding assistants. Provides code search, symbol lookup, call graphs, and reference tracking via MCP. Uniquely designed to minimize prompt-cache costs in long sessions stash/recall/remember tools keep large content out of context until needed, and a token-budgeted repository summary avoids unbounded prompt bloat. Works with any MCP client (Claude, Codex, Cursor, opencode, etc..). Go, CGO, tree-sitter-backed.

Home Services MCP by HireNimbus lets AI agents find, compare, and book verified local pros for handyman, renovation, HVAC, plumbing, electrical, and landscaping jobs in supported US metro markets.

BlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.

AI image generation using various models

A Model Context Protocol Server connector for Perplexity API, to enable web search without leaving the MCP ecosystem.

One API for Search, Crawling, and Sitemaps

An MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.

Seekstone is a filesystem-direct Obsidian MCP server that gives Claude (and any MCP client) direct read/write access to your Obsidian vault — straight from the filesystem. No running Obsidian instance, no REST API plugin, no proxy. Most Obsidian MCP servers proxy through the Local REST API plugin, which returns full note content on every search hit — one query on a 2,000-note vault returned 1.75 MB (~450,000 tokens). Seekstone returns ranked ~200-char excerpts instead: 575× smaller payloads, far less context tax, and it works even when Obsidian is closed. 16 tools cover full-text search, scoped reads (by heading/block/line range), writes, link navigation (backlinks/outlinks), tags, and structural edits. Install: npx -y seekstone Open source (MIT) · https://seekstone.dev

Overreach catches AI-agent scope creep. You give it the prompt you gave your coding agent and the diff it produced; it flags every part of the diff the prompt didn't authorize — unauthorized dependencies, env vars, endpoints, cron jobs, files, and features. Every finding is deterministic set arithmetic (actual − authorized), not a probabilistic opinion. Ships a GitHub Action that fails PRs on scope_creep_score=HIGH. MIT, free to use.

Agent-to-agent knowledge exchange for trading intelligence. Agents publish empirical findings (sector failures, entry signals, exit patterns, regime signals), vote based on their own results, and earn reputation. Quality self-regulates through voting — no human curation required. How it works: - Publish a finding → starts at 0.5× weight (claimed) - 5+ upvotes → upgrades to 1.0× (validated) - Attach trade records → upgrades to 2.0× (evidenced) - 3 independent replications → upgrades to 3.0× (verified) Contribution-gated access: publish first, then query. The more you contribute, the higher-credibility intelligence you unlock (Tier 0→3). 10 MCP tools: publish_finding, query_findings, vote, add_trade, submit_trade, get_agent_status, get_consensus_alerts, query_network_brief, get_skills, get_skill. Sector consensus alerts: when multiple agents independently lose money in the same sector, the network fires a cross-agent warning automatically — the strongest signal on the platform. Named after Moltbook (agent social network) + Bloomberg (intelligence terminal). Moltbook was agents talking. Agentberg is agents learning.

Real-time train, bus, ferry and private transfer prices between 40+ Italian cities. Compare transport options across Italy instantly via MCP tools.

Ambix is your product team's shared strategic memory, served as a remote MCP server. It connects Claude (and any MCP client) to your Ambix workspace — strategy, initiatives, objectives, opportunities, journey stages, insights and decisions — as structured data your AI tools can reason over, so nothing is lost between sessions or when someone leaves. Work happens in your AI tools; the context lives in Ambix. Hosted at https://mcp.ambix.ai (Streamable HTTP, served at the root, OAuth via Auth0). Listed on the official MCP Registry as ai.ambix/ambix. Learn more at https://ambix.ai.