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Reqode

Gives AI coding agents connected requirements and architecture context to build whole features, then helps teams verify implementation against specs.

Reqode is a software engineering platform designed to bridge the gap between product requirements, system architecture, and AI-assisted implementation. When teams delegate development tasks to AI coding assistants, agents often lack full architectural context and holistic product understanding, leading to code divergence and architectural drift. Reqode addresses this challenge by maintaining a living, branch-aware model of specifications and implementation rules.

The platform structures requirements into interconnected models spanning data entities, API operations, interface designs, and test suites. Rather than relying on fragile manual prompts, development teams can define feature requests through structured change requests. These change requests tie functional targets directly to relevant code units and architectural constraints.

Through dedicated Model Context Protocol servers, Reqode exposes focused, high-fidelity context directly into agentic coding environments such as Cursor, Claude Code, and Cline. Coding agents receive exact boundaries and specifications before writing code. Following implementation, automated verifiers check the generated source against established system guidelines and record traceable verification evidence.

Reqode supports both cloud-hosted environments and self-hosted on-premises deployments using Docker containers. The platform accommodates individuals, startups, and enterprise engineering teams seeking to harness autonomous software delivery without sacrificing engineering rigor, traceability, or architectural integrity.

Features

  • Connect requirements, data models, UI and API specifications, code, and tests.
  • Review specification changes through scoped Change Requests and branches.
  • Give external coding and QA agents engineering context through MCP.
  • Flexible deployment options including cloud-hosted plans and isolated on-premises self-hosting via Docker

Use cases

  • Define whole features with connected data, UI, API, and architecture context.
  • Prepare scoped Change Requests and review specification changes with the team.
  • Review implementation Findings and test evidence against specifications.
  • Deploying governed AI development workflows within private enterprise networks using self-hosted Docker instances

Screenshots

Reqode screenshot Reqode screenshot

Frequently asked questions

Which coding agents can I use?

You can use MCP-compatible agents such as Codex, Cursor, or Claude Code within your coding environment.

Can organizations host Reqode on their own private servers?

Yes, Reqode offers a self-hosted Docker deployment starting at $3,000 per instance annually, allowing teams to use their own private AI API keys.

Can coding agents edit specifications through MCP?

Coding MCP provides engineering context and lets agents create and resolve Findings without editing specifications. Teams review specification changes separately.

Where is cloud data stored and processed?

Reqode cloud infrastructure is hosted in European Union data centers operated by Hetzner Online GmbH in compliance with GDPR standards.

Does Reqode offer a free tier?

Yes, the Startup plan is completely free for up to three licensed users and up to three projects, with optional pay-as-you-go AI credit packs.

What we verified

Public API
No (Integrations are powered via Model Context Protocol servers rather than a public developer REST API)
Self-hostable
Yes (Docker-based self-hosted enterprise deployment starting at $3,000 per instance per year)
Free tier
Yes (Free Startup plan supporting up to 3 licensed users and 3 projects)
Pricing model
Freemium / Subscription
Price
$0 (Startup plan), $9/user/month (Cloud Starter), $19/user/month (Cloud Pro), or $3,000/instance/year (Self-hosted)
Data region
European Union (Cloud infrastructure hosted on Hetzner Online GmbH in Germany/EU; customer-controlled on self-hosted instances)
Integrations
Model Context Protocol (MCP), Cursor, Claude Code, Cline, OpenAI Codex, Git, GitHub, Docker

Could not be verified

Complete catalog of pre-built verification rules available out of the box
Specific automated test runner frameworks integrated directly beyond manual test management
Exact latency benchmarks for MCP context retrieval across large-scale monorepos

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