"Querying Elasticsearch (ES)" matching MCP servers:

Description Governed agent city-state. Register as an agent, browse open mission slots, earn revenue under constitutional protocol. Every action creates a SHA-256 provenance seed. Powered by MO§ES™.

Enables AI agents to manage tasks through a structured lifecycle (todo, in_progress, ai_testing, manual_testing, deployment, completed) with human approval gates, providing a single-user task management system with CLI, REST API, and live updates.

Implements a distributed AI worker pattern over MCP, enabling clients to register as workers, poll for tasks, process prompts with AI, and submit results back to the server continuously.

Exposes a running DeepSeek Harness as an MCP endpoint so any other agent or script can create workspaces and sessions, hand coding tasks to the DSH agent, read and write files, run shell commands, and invoke permitted harness tools under the same sandbox, transcript, and permission policy as the DSH UI.

Production-ready integration of Microsoft Agent Framework with MCP, enabling AI agents to access tools like weather queries, calculations, and Taiwan stock prices through SSE/HTTP streaming transport with Azure OpenAI GPT-4 backend.

Pluggable local agent capability hub that gives web-based DeepSeek local Agent capabilities (MCP/file operations/skills/desktop automation) and lets local agents reuse the same tools.

A sovereign, MIT-licensed MCP server for professional-service workflow automation, enabling offline-capable, cryptographically signed operations without vendor lock-in.

Enables AI agents to spawn, coordinate, and message worker cells via a single MCP server over a local Unix socket.

A sovereign, MIT-licensed MCP server wrapping the fallhome-us-sdk, enabling autonomous agents and developers to interact with the FallMarket ecosystem through Ed25519-signed operations.

Enables any MCP client to watch a running DSH agent and steer it mid-flight, streaming thinking, tool and file notifications while sharing intent and exposing a floor lock that denies the agent's writes while held. It also lets clients interrupt the current turn with an injected alert and delegate reviews through an on-disk inbox.

Sovereign, MIT-licensed MCP server wrapping the fallvet-us SDK for offline-capable professional workflow tools.

A Model Control Protocol server that integrates with Claude Desktop to enable simultaneous querying and cross-checking of responses from multiple LLM providers including OpenAI, Anthropic, Perplexity AI, and Google Gemini.

Listens for Slack @mentions and publishes them as real-time events to the KĀDI event bus, enabling event-driven architectures with low latency.

hermes-mcp-s is a modular MCP suite host for Hermes and other agents. It provides one stdio MCP server that can load long-lived personal automation capabilities as installable external modules.

Enables Codex to read a project's kickoff card, acceptance criteria, AGENTS rules, handoff package, progress, Git trail, and next step, and to append validated, audited, idempotent progress events backed by a matching project-record Git commit. Access is scoped to one workspace and project via short-lived, revocable, hash-stored credentials that cannot reach members, keys, deletion, publication, or deployment.

Enables MCP clients to read a project's Git-backed kickoff, acceptance criteria, handoff package, progress, and next step, and to append validated, audited progress events as project records. It provides short-lived scoped credentials and fail-closed tool allowlisting for safe, resumable AI-assisted development.

Comprehensive quest orchestration system with KĀDI broker integration, multi-channel approval workflow, and Git-backed data storage.

A lightweight Model Context Protocol server that enables creating, managing, and querying model contexts with integrated Datadog metrics and monitoring.

Aggregates tools from multiple MCP servers, generates TypeScript definitions, and executes custom TypeScript scripts to orchestrate cross-server tool calls.

Read-only MCP server that exposes the agentic-os governance, SDLC, and Quality Engineering methodology to any MCP host. It never writes to your repository and never executes code — it serves the methodology, plans an install, and verifies it, handing any commands back to the host to run.

A local stdio MCP service that unifies coding agents like Codex and Claude into cs_agent_* tools, enabling the root agent to create, invoke, and manage child agents with recursive delegation.

Provides a JSON-RPC MCP server that exposes policy-governed agent tools, including paid tools, tool muxing, and OpenAPI-to-MCP conversion, enabling agents to discover, coordinate, and execute tasks within the ProtoOS ecosystem.

AgentBridge is a local MCP server that lets Claude Code delegate coding tasks to external CLI workers like Codex and Antigravity. It assembles structured prompts, runs the workers with git snapshotting, and returns compact structured results without running its own models.

Enables MCP clients to drive ChatGPT's web interface through a built-in persistent browser, requiring only a single manual login. Prompts are sent through temporary incognito chats and the captured answer text is returned as tool results, along with live model listing, login/status probing, and optional HTTP transport.

MCP server that exposes a pool of Claude SDK agents as tools, enabling deterministic agent creation, retrieval, and resumption from a capability corpus.

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.

Lets coding agents share a local dev server or upload a built site at a public https link (ouicu.com), and hand the link back. Works with Claude Code, Cursor, Codex, VS Code and Windsurf.

Discover which MCP servers can interact with real-world entities like restaurants, hotels, and salons by querying the Dock AI registry using domain names.

Enables querying multiple AI models in parallel (Claude, Gemini, O3) and synthesizing their responses using anonymous analysis to reduce bias, providing a comprehensive answer.

Provides MCP tools to migrate or compress conversation sessions between models based on context window capacity, including querying model context windows and listing known models.