"Requesting an answer from a specific document" matching MCP servers:

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

An authenticated OpenAI-compatible inference gateway with an async job broker that bridges a coding agent to a ChatGPT MCP worker, enabling ChatGPT to process inference requests via a tunnel.

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

Long-term memory for Claude Desktop and Claude Code over plain markdown files on your machine. It returns nothing when the corpus has no answer, naming the terms that appear nowhere — no least-bad match dressed as an answer. And it verifies cited commit SHAs against git, so an agent can tell what actually shipped from what was only discussed and abandoned. Local; nothing is transmitted.

An MCP server that connects Claude Desktop to an interactive Claude Code session running in a tmux terminal.

An MCP server that reverse-engineers a rebuild spec (CLAUDE.md, config, and mutation-tested tests) from an existing app, enabling coding agents to rebuild the app cleanly against that spec.

Provides coding agents with repository context through tools that generate AGENTS.md files or structured JSON summaries, quoting build/test commands from the repo's manifests for a small fee without an API key.

An autonomous virtual software agency MCP server that generates production-grade software projects from a description, with 27 senior personas debating and cross-examining every artifact.

An MCP server that allows coding agents to look up contextual rules and patterns on demand, providing just-in-time guidance for specific tasks like writing tests or authoring UI.

Bridges MCP clients such as Claude Code and Cursor to independent Codex app-server sessions, letting them start, poll, steer, review, compact, cancel, and answer prompts for asynchronous Codex tasks over local stdio or a remote authenticated WebSocket. Runs read-only by default, with workspace-write sandboxing only when a user explicitly enables it, and reports job status, model listing, and progress back to the client.

Delegates heavy development tasks from a supervisor to an autonomous worker on a cheaper model via MCP, with isolated git worktrees and provider-agnostic support.

Agentic MCP server that receives a feature specification from an IDE, autonomously implements it in an isolated sandbox via an internal loop (plan-act-validate-correct), and returns a structured report with diffs and test results, without modifying the original repository.

An MCP server for orchestrating Google Jules as a remote coding agent from a local coding agent, handling task decomposition, API dispatch, monitoring, intervention, code review, and PR merging.

An MCP server implementing a 7-stage agentic frontend workflow—from design audit to PR review—including AI-driven component generation, browser validation, E2E testing, and CI self-healing.

An MCP server that owns the harness: your project's constitution, structure, design rules, requirements and phased tasks. The agent reads it, writes code from it, and may only propose changes to it.

An MCP server that gives AI assistants tools to generate AccelByte AGS uGUI prefabs in Unity projects, look up AccelByte Unity SDK best practices, search Bytewars C# example components, and configure SDK credentials from a Claude Code or Cursor session.

An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.

Service-boundary-aware document exchange center for coordinating heterogeneous LLM code agents via MCP. Versioned Markdown store, pub-sub notifications, and diff-aware update protocol.

Rewrites coding prompts for optimal results with AI IDEs like Cursor by using Claude to add structure, context, and language-specific considerations to user prompts.

Integrates the Atlassian Rovo Dev CLI with the Model Context Protocol, allowing AI assistants to perform deep code analysis using Rovo Dev's large context capabilities. It enables features like repository-wide queries, file-specific analysis, and specialized coding modes through a standard MCP interface.