"A resource or repository of information and knowledge" matching MCP servers:

Manages resource allocation, MCP server lifecycle, and Kubernetes workers in cortex automation systems. Provides tools for requesting/releasing job resources, starting/stopping/scaling MCP servers, and provisioning/destroying burst workers with TTL management.

MCP server providing virtual memory for AI context with durable SQLite storage, retrieval, and bounded prompt assembly to manage context windows.

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

A meta-server that aggregates multiple MCP servers into a single interface, reducing token usage by 98%+ through progressive tool discovery and direct code execution that processes data between tools without consuming context window space.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

A multi-agent orchestration system that enables multiple Claude instances to collaborate through a centralized hub with a shared workspace and real-time communication. It features integrated task management, role assignment, and persistent memory to facilitate complex, synchronized agent workflows.

A Cloudflare Workers-based service that enables intelligent searching, automatic code snippet recording, and statistical analysis of programming knowledge stored in Notion databases.

Enables Large Language Models to analyze GitHub repositories in real-time, providing tools for retrieving repository information, analyzing issues, accessing documentation, and visualizing activity.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Lets AI agents register, post job specs to matching specialist bots, authorize PayPal escrow funds, and capture payment only for units that pass acceptance checks. Covers the full job lifecycle — bidding, hashed contracts, funding, delivery verification, payouts, dispute mediation and long-polled events.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Enables federated search across public ARD registries and a verified index of MCP tools read from each server's own tools/list, with hybrid lexical and semantic retrieval. It lets agents discover and connect to resources at runtime without hard-coded integrations.

Provides a unified MCP/A2A endpoint that fans out to multiple LLMWiki Knowledge Sources, synthesizes answers with citations and trace steps, and optionally calls an OpenAI-compatible runtime for grounded responses.

Enables AI agents to securely reach enterprise tools and other agents through a governed gateway with pinned tool definitions, delegated authorization, content inspection, human approval, and signed audit trails.

Enables a Claude Code cloud session to run shell commands inside a chroot jail on your own computer and to call the MCP servers already installed there, with every request authenticated and relayed over a Cloudflare quick tunnel so no router port is opened and no SSH key or tunnel is ever handed to the cloud VM.

Enables autonomous coding agents to check memory, CPU, and disk headroom before heavy work, emitting cgroup-aware NEAR_OOM_THRESHOLD alerts that let them back off before an OOM kill or context blowup. It also scans a workspace for token-heavy, low-value paths such as dependency trees, build output, logs, and bundles, returning ranked findings and ready-to-paste exclude_globs to keep them out of the agent's context.

A Model Context Protocol (MCP) server that provides persistent memory and context management for AI systems through a structured 5-phase optimization workflow.

An MCP Server that provides access to League of Legends statistics via the SportData.io API, allowing agents to query and analyze LoL competitive gaming data.

Enables context optimization for LLM-powered coding assistants by compressing prompts, injecting task protocols, and providing a 2nd Brain knowledge graph with tools for prompt compression, knowledge retrieval, metrics, and runtime configuration.

Provides MCP tools to create and query SigNoz trace funnels, enabling agents to measure their own step conversion rates from within the agent loop.

Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

Enables coding agents to consult other coding-agent CLIs for independent opinions on proposals, receiving per-agent responses that can be verified and recorded without sharing conversation history.

Just to be clear about the final JSON: the MCP server is named herdr-inbox, and it enables Claude Code agents in herdr to ask questions asynchronously without stalling, with all open questions answered from one popup and answers routed back to the asking agent.

Enables AI assistants to interact with the QuantConnect cloud platform for algorithmic trading. Supports creating and managing trading strategies, running backtests, deploying live algorithms, and performing comprehensive trading operations through the QuantConnect API.

Enables AI agents to claim, heartbeat, submit, split, park, and resume atomic work-queue tasks, with fencing tokens and receipts, while storing and versioning records and content-addressed files through MCP.

Exposes Amazon Nova Act web automation capabilities through the Model Context Protocol, enabling AI agents to perform browser tasks like navigation, data extraction, and form interaction.