"All items" matching MCP servers:

Lets AI agents search and discover skill files from a curated catalog to fill missing capabilities, providing download URLs for free items and purchase info for paid ones.

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 orchestrating multiple AI CLI agents (Claude Code, Codex, Gemini CLI, Copilot CLI) through a unified MCP interface for task delegation, cross-agent comparison, and specialized tools like code review and debugging.

Enables building, optimizing, reviewing, and running AI agents and skills, plus managing authorized work items, in Erstan's QA environment via OAuth-authenticated MCP.

A proxy that reduces context token waste by exposing meta-tools (search_tools, load_tool, unload_tool) so the agent loads only needed tool schemas instead of all upstream tools.

Exposes only two meta-tools that discover and invoke backend MCP servers on demand, reducing context bloat while keeping all configured tools available.

Orchestrates Fireflies, Asana, and Notion MCP servers to automate end-to-end meeting workflows. Enables users to search meetings, extract action items, create tasks, and generate meeting documentation through natural language commands.

Provides tools for AI coding agents to read and write shared team context, including status, pending items, and handoffs. Enables agents to query current project status and claim pending work.

An MCP server that enables Claude to interact with Port.io's AI agent, allowing users to trigger the agent with prompts and receive structured responses including status, output, and action items.

Acts as the agent-side front door to the kingdom, providing tools to map services, check live status, detect FOMO, and access the agent marketplace, all through a single MCP connection.

Enables MCP clients to call the app's REST endpoints as tools for listing, retrieving, and creating items, plus health checks, over Streamable HTTP. Destructive delete operations are excluded by default.

MCP server that lets AI agents manage an Agent Inbox queue via natural language. It supports listing pending items, adding new URLs with notes, and marking items as reviewed or deleted.

Enables agents to build and maintain recursive task trees with live browser progress, isolated per-conversation work items, and verification gates that require explicit acceptance evidence.

Provides a durable SQLite-backed work queue for AI agents, enabling creation, claiming, starting, handing off, failing, and completing work items via MCP tools.

Enables AI agents to exchange structured work items with an auditable lifecycle, supporting send, acknowledge, block, complete, and cancel operations via a shared SQLite-backed inbox.

One MCP to rule them all. A single MCP endpoint that aggregates many downstream connectors — remote MCP servers and plain HTTP APIs — and presents agents a fixed set of nine meta-tools.

A single MCP endpoint for AI agents to browse, inspect, and call tools from multiple upstream MCP servers without loading all schemas upfront, reducing context overhead.

Governs and manages Qwen Code builder sessions with tools for previewing, starting, inspecting, queuing tasks, and stopping sessions, all within a scoped, redacted environment.

Connect your AI models to your favorite SurrealDB database, and let the LLMs do all your work for you.

Enables multiple concurrent MCP clients to safely share one backend MCP server by terminating client sessions, serializing forwarded calls, and mirroring the backend's exact tools and schemas. It also reconnects automatically if the backend restarts or drops, exposing a status tool for reachability checks.

Acts as a proxy for multiple MCP servers, reducing context window usage from 15,000+ tokens to ~500 tokens by dynamically loading servers on-demand and exposing only 3 tools instead of all tool definitions.

Enables Claude to cheaply bulk-screen 30 or more short items (repo blurbs, issue titles, log lines, grep hits, test names) against one crisp yes/no criterion, using Jev to sort them into clear_yes, uncertain and clear_no buckets instead of spending its own tokens on each. It supports inline items or a project-local .json/.jsonl file read server-side to keep context cost low, while treating results as advisory only.

Enables AI agents to submit work for human review over MCP or REST, then retrieve approvals, edits, or change requests without blocking. Reviewers can approve, edit, or send back items from a web or phone interface.

Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what agents must produce — the server blocks the call if they don't. Works with any MCP-compatible client.

Expose all Home Assistant voice intents through a Model Context Protocol Server allowing home control.

Enables any MCP host to start, log, and end agent sessions and export them as a normalized, redacted timeline while keeping all data local.

Capytail is a local MCP capability router that selects relevant skills before loading context, enabling efficient routing without executing or loading all skills upfront.

Enables sandboxed chatbots to access all 44 Agentora plugin tools through a single MCP endpoint with one OAuth connection.

Liminal turns objectives into structured work by strategizing through an atomic, deterministic basis: setting guardrails around scope, compiling resources and constraints, uncovering gaps, and organizing research and next steps. All while carrying continuity and priorities forward so your AI builds on what’s already done.

Single gateway that aggregates dozens of upstream MCP servers, enabling AI clients to connect once and access all tools.