"Terraform - Infrastructure as Code Tool or Related Search" matching MCP servers:

A Model Context Protocol (MCP) server that integrates Claude with the Terraform Cloud API, allowing Claude to manage your Terraform infrastructure through natural conversation.

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.

Enables dispatching entire autonomous multi-agent engineering swarms directly from IDEs like Cursor and Windsurf via a single MCP endpoint, with streaming progress updates and verified git diffs returned to the editor.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

A standalone MCP gateway/proxy server that lets any MCP-compatible client search and call tools across multiple downstream MCP servers through a single mcp proxy tool.

MCP server that routes natural language requests to structured tool calls using a LoRA-tuned small language model, with built-in validation, retry, and fallback recovery.

Enables agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.

Enables multi-agent council workflows for coding assistants, providing parallel independent reviews, plans, brainstorms, validation, and research with strict read-only boundaries.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Universal search engine for AI agents. Discover products, services, and businesses across every category. 10 MCP tools, zero LLM calls, millisecond responses.

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

A single MCP server that provides dynamic access to thousands of APIs through discovery and proxy, eliminating the need to install and configure multiple separate MCP servers.

Media Execution Control Layer for AI Agents. Reserve-execute-burn/refund pattern. FFmpeg post-processing (format conversion, audio normalization) Supports Flux2 Pro, Veo 3.1, Suno V5.

Enables centralized proxy and orchestration of MCP servers, providing unified tool discovery, authentication, and secure request routing. It adds a human-in-the-loop approval gate for high-risk actions and audit logging.

Enables AI agents to perform web search, extraction, and research across multiple provider backends with persistent multi-key rotation and auditable routing. Supports MCP, CLI, and Agent Skill entry points.

Enables declaring a catalog of tools for LLMs, filtering them by role, validating arguments, guarding sensitive calls with server-side confirmations, and recording an audit log.

Routes external MCP tools behind a small on-demand discovery interface for Codex agents, using Jev to select relevant tools and providing fallback to the full inventory when confidence is low.

Enables locally configured MCP servers to be called over stdio and mixed with xAI server-side tools, without relying on hosted xAI MCP.

Enables parallel research across multiple cheap AI worker models, splitting a question into sub-questions and synthesizing one sourced answer with references.

Lets agents run a small JavaScript program in a sandboxed worker that composes typed Jev judgments — claim checking, text screening, best-item picking, label classification, passage comparison, and yes/no questions — in a single call, returning only schema-validated results. A companion search tool exposes each judgment's JSON input and output schemas.