Specflow

Agentic Harness for Large-Scale Code Generation

[](LICENSE) [](https://pypi.org/project/gd-specflow/) [](https://www.python.org/downloads/) [](https://github.com/griddynamics/specflow/actions/workflows/publish-mcp.yml)

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AI agent harness for automated code generation and complexity estimation. Multiple deployable codebases built by multiple SOTA AI models. When their code complexity scores align, it proves the specs are complete.

SpecFlow is an AI agent harness that automates code generation, deployment, and testing through parallel AI agents in isolated, sandboxed execution environments.

Validator agents continuously assess, resume, and refine work until delivery standards are met.

https://github.com/user-attachments/assets/0783c394-1bf0-449f-a36e-1d46e899661c

Getting Started

Software

| Requirement | Notes | | ----------- | ------------------------------------------------------------------------------------------------------------ | | Docker | Container runtime for the harness sandbox. Install Docker | | uv | Python package manager. Install via brew install uv or see docs | | IDE | SpecFlow is used as MCP in a IDE with agentic AI enabled: Cursor, Claude Code, Copilot, Gemini etc. This is the users project. |

Keys and Tokens

| Key | Name in .env | Notes | | ---------------------------- | ------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | | GitHub Personal Access Token | GITHUB_TOKEN | For disposable workspace repos. Scope: repo + read:user + workflow repo,read:user. Advan | | P10Y API key | P10Y_API_KEY | Code complexity scoring. [Setup guide](docs/quickstart-compass.md) | | LLM provider key | OPENROUTER_API_KEY or ANTHROPIC_API_KEY | One key required. Get OpenRouter key (default) or Get Anthropic key |

Installation

Few simple steps to get you going:

• clone repo

``sh git clone https://github.com/griddynamics/specflow.git && cd specflow ``

• install Specflow (includes the Terminal UI that guides you through onboarding)

``sh uv tool install --editable ./mcp_server ``

• start Specflow app and follow instructions

`` specflow tui ``

> [!Important] > Specflow Harness Sandbox is now running locally. > Easiest: in specflow tui, press c (Add MCP to AI tool) — the setup screen detects > Claude Code, Gemini CLI, and Cursor and wires SpecFlow up for you (one key), with an honest > connected/added/failed status per client. > Prefer to do it by hand? Copy-paste the content of .specflow-local/mcp-config.json into your client.

Cursor Claude Code Claude Desktop Copilot Gemini CLI

...and any other IDE or client that supports the Model Context Protocol.

Usage

MCP is now ready to use in any project. Prompt your IDE agent to talk to the harness.

Let's say specification files are in specs directory, you can follow these steps:

1. Start a new project in IDE and put your specs files into specs directory

``text specs/ |-- product-requirements.md |-- user-flows.pdf \-- acceptance-criteria.md ``

1. Check your specification completeness using check_specification_completeness tool

``text Use SpecFlow MCP to check specification completeness in specs directory ``

1. Create a detailed plan using our run_planning tool

``text Create implementation plan using SpecFlow MCP ``

1. When you are happy with the plan, run generation using run_generation as above

``text Run generation with SpecFlow MCP ``

1. Generation usually takes many hours, use our TUI to monitor progress and receive Desktop Notifications:

``sh # Any terminal specflow tui ``

1. When the generation has been completed, you can retrieve the results and P10Y reports from harness:

``text Download outputs using Specflow MCP `` The rule of thumb is: if the P10Y score spread is low, then your specification is ready!

1. Use the built-in prompt to compare the variants and identify their strong and weak sides, together with a plan to automatically assemble the best variant.

``text use SpecFlow MCP prompt: specflow-compare-variants ``

MCP Tools

| Tool | Description | | ---------------------------------- | ----------------------------------------------------------- | | check_specification_completeness | Analyze specs for gaps and contradictions (local) | | run_planning | Generate a phased implementation plan (local) | | read_document | Extract PDF/DOCX/PPTX/XLSX/CSV to markdown (local) | | run_generation | Upload and launch parallel codegen on the backend (2-8 hrs) | | check_status | Poll generation progress | | download_outputs | Download archived artifacts from a completed run | | retry_generation | Retry a failed generation |

If you want to go deeper

SpecFlow Detailed Overview

https://github.com/user-attachments/assets/ea1dd95d-5742-4c51-bf2c-c2cb582669c3

Full MCP config and usage: [MCPUSER.md](MCPUSER.md)

Full MCP API reference: [docs/mcp/APIREFERENCE.md](docs/mcp/APIREFERENCE.md)

Detailed SpecFlow harness instructions: [QUICKSTART.md](QUICKSTART.md)

> [!Important] > AI agents work in scratchpad repos that are reset before each run — we create them for you. > Do not point SpecFlow at repositories with code or history you want to keep. > The managed SpecFlow service is for Grid Dynamics employees only. Open-source users should run the local quickstart.

Documentation

| Document | Description | | ------------------------------------------------------------------------ | ------------------------------------------- | | [QUICKSTART.md](QUICKSTART.md) | Local setup and first run | | [CONTRIBUTING.md](docs/CONTRIBUTING.md) | How to contribute — workflow and PR checklist | | [CLAUDE.md](CLAUDE.md) | Development protocol and STEEL commandments | | [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md) | System design and data flow | | [docs/mcp/APIREFERENCE.md](docs/mcp/APIREFERENCE.md) | MCP tool reference | | [docs/backend/DEVELOPMENT.md](docs/backend/DEVELOPMENT.md) | Backend development guide | | [docs/backend/APIREFERENCE.md](docs/backend/APIREFERENCE.md) | REST API reference | | [docs/operations/TROUBLESHOOTING.md](docs/operations/TROUBLESHOOTING.md) | Troubleshooting guide | | [docs/IDE-SETUP.md](docs/IDE-SETUP.md) | IDE configuration (Cursor + Claude Code) | | [docs/examples/deployment-spec-example.md](docs/examples/deployment-spec-example.md) | Example spec for agentic deployment + E2E tests | | [SECURITY.md](SECURITY.md) | Security policy and vulnerability reporting |

Contact

Questions, feedback, or anything that doesn't fit a GitHub issue: [specflow@griddynamics.com](mailto:specflow@griddynamics.com)

Found a security vulnerability? Please report it privately per [SECURITY.md](SECURITY.md) rather than opening a public issue.

License

[MIT](LICENSE) — Copyright (c) 2024 Grid Dynamics International, Inc.

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Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: griddynamics
• Source: griddynamics/specflow
• License: MIT

Install and usage instructions live in the source repository linked above.