Overture
About
Visual plan approval for AI coding agents. See your agent's plan as an interactive graph, attach context, choose approaches, then approve before any code is written.
Details
- Author
- sixhq
- Categories
- Developer Tools
Jump to
Setup
Install Overture in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/sixhq/Overture
Follow the installation instructions in the repository README, then restart your MCP client.
- Review and approve AI-generated plans before code execution— Overture renders the agent's plan as an interactive flowchart viasubmit_planand waits for your approval throughget_approval.
- Monitor execution progress in real time— watch nodes update status (update_node_status) as the agent runs, with visual indicators for pending, active, completed, and failed steps.
- Pause, resume, or re-run plan steps— usecheck_pauseandcheck_rerunto control execution mid-flow without losing context.
- Resume past plans from history— callget_resume_infoto reload a saved plan with all field values, branch selections, and attachments preserved.
- Modify plans dynamically during execution— insert, remove, or replace nodes viarequest_plan_updateand review changes in the plan diff view.
See the plan before the code. Approve it. Then watch it execute.
Problem•Solution•Install•Features•Marketplace•Config•Discussions
https://github.com/user-attachments/assets/eeb9c4cb-c80d-42da-bf63-c0c4ecb1e5d6
Every AI coding agent today —Cursor,Claude Code,Cline,Copilot— works the same way:
- You type a prompt
- Agentimmediately starts writing code
- You havezero visibilityinto what it's doing
- You realize it misunderstood your request
- Hundreds of lines of codeneed to be discarded
- You've wasted tokens, time, and patience
Some agents show plans as text in chat. But text fails to show:
- Dependencies— which tasks depend on what?
- Branch points— what alternative approaches exist?
- Context requirements— which files, APIs, or secrets are needed?
- Complexity— which steps are risky?
- Progress— what's done, what's next?
Overtureintercepts your AI agent's planning phase and renders it as aninteractive visual flowchart— before any code is written.
The agent doesn't write a single line of code until you approve the plan.
Overture is an MCP server that works withany MCP-compatible AI coding agent. One command to install.
claude mcp add overture-mcp -- npx overture-mcp
{ "mcpServers": { "overture": { "command": "npx", "args": ["overture-mcp"] } } }
Open VS Code settings → search "Cline MCP" → add:
{ "mcpServers": { "overture": { "command": "npx", "args": ["overture-mcp"] } } }
Create.vscode/mcp.jsonin your project root:
{ "servers": { "overture": { "command": "npx", "args": ["overture-mcp"] } } }
Note:GitHub Copilot MCP requires VS Code 1.99+ and usesserversinstead ofmcpServers.
{ "mcpServers": { "overture": { "command": "npx", "args": ["overture-mcp"], "disabled": false } } }
Give your agent any task. Overture automatically opens athttp://localhost:3031with your plan ready for approval.
Click any node to reveal its full details:
Nodes can request input from you before execution:
- Required/optional indicator
- Default values
- Help text & descriptions
- Setup instructions ("How to get an API key")
- Automatic type detection— Image, code, document, or other
- Visual iconsper file type
- Descriptions— add notes about why this file matters
- Delete— remove unwanted attachments
Add custom LLM instructions to any node:
"Pay special attention to error handling here" "Use the existing auth pattern from src/auth.ts" "Make sure to add tests for edge cases"
Instructions are sent to the agent right before that node executes.
When the agent proposes multiple approaches:
Before you can approve, Overture shows what's needed:
- Empty required fields— counted per node
- Branch selections— which decisions are pending
- Progress indicator— visual completion tracking
- Expandable items— click to see details
- Color coding— Green (done) / Orange (pending)
The Approve button stays disabled until all requirements are met.
- 🟢"Approve & Execute"— plan ready, requirements met
- 🟠"Complete Requirements"— conditions unmet
- 🔵"Executing..."— running with spinner
- 🟢"Completed"— all done
- 🔴"Failed"— error occurred
After each node executes, see rich structured output:
Each category isexpandable— drill in without visual overload.
Click any completed node to see full output:
- Scrollablefor long outputs
- Syntax highlightedcode snippets
- Close with Escapeor click outside
Browse and attach MCP servers directly from the Overture UI.
When you attach an MCP server to a node, the agent gains access to those toolsonly for that step.
Work on multiple projects simultaneously:
Single project? Tab bar hides automatically for a cleaner UI.
When resuming, you get complete context:
- Current node— where execution stopped
- Completed nodes— with their outputs
- Pending nodes— what's left to do
- Failed nodes— with error messages
- All configurations— field values, branches, attachments
- Timestamps— when created, when paused
When a plan changes, see exactly what's different:
- Added nodes— highlighted green
- Removed nodes— highlighted red
- Modified nodes— yellow with before/after comparison
- Edge changes— added/removed connections
Overture exposes 11 MCP tools for agents to interact with:
connected•plan_started•node_added•edge_added•plan_ready•plan_approved•node_status_updated•plan_completed•plan_failed•plan_paused•plan_resumed•nodes_inserted•node_removed•project_registered•projects_list•history_entries•plan_loaded•resume_plan_info•plan_updated
When the WebSocket port is already in use, Overture automatically operates as arelay client, forwarding messages through the existing server. Multiple agent instances can share a single UI.
claude mcp add overture-mcp -e OVERTURE_HTTP_PORT=4000 -e OVERTURE_AUTO_OPEN=false -- npx overture-mcp
{ "mcpServers": { "overture": { "command": "npx", "args": ["overture-mcp"], "env": { "OVERTURE_HTTP_PORT": "4000", "OVERTURE_WS_PORT": "4001", "OVERTURE_AUTO_OPEN": "false" } } } }
{ "servers": { "overture": { "command": "npx", "args": ["overture-mcp"], "env": { "OVERTURE_HTTP_PORT": "4000", "OVERTURE_WS_PORT": "4001", "OVERTURE_AUTO_OPEN": "false" } } } }
Each agent hascustom-tailored promptsfor optimal plan generation.
- Transparency— See exactly what happens before code is written
- Control— Approve, reject, or modify any plan
- Context— Attach files and instructions to the right steps
- Choice— Compare approaches and pick your path
- Visibility— Real-time progress with rich output
- Safety— Pause, resume, or re-run at any time
- History— Resume any past plan instantly
- Efficiency— No wasted tokens on rejected approaches
- Trust— Makes agents predictable and controllable
- Interpretability— See AI reasoning before execution
- Universal— Works with any MCP-compatible agent
- Extensible— MCP Marketplace for tool discovery
- Open Source— MIT licensed, community-driven
- Self-Contained— No cloud dependencies
- Works Offline— Fully local execution
- Multi-Project— Manage multiple workspaces
# Clone the repo git clone https://github.com/SixHq/Overture.git cd Overture # Install dependencies npm install # Build all packages npm run build # Start MCP server (in one terminal) cd packages/mcp-server && npm start # Start UI dev server (in another terminal) cd packages/ui && npm run dev
Overture is open source and we welcome contributions!
- 🐛Report bugsatGitHub Issues
- 💡Suggest featuresatGitHub Discussions
- 📖Improve docs— PRs welcome
- 🔧Contribute code— seeCONTRIBUTING.md
All contributions are appreciated, no matter how small.
Built bySixth
For the best experience, trySixth for VS Code
Overture is built-in with zero configuration required.
Stop flying blind. See the plan. Approve it. Execute with confidence.
This is a web browser that enables your coding agent, such as Claude Code, to visit websites on your behalf and assist you in identifying bugs or creating UI test cases.
Create crafted UI components inspired by the best 21st.dev design engineers.
Bring agent evaluations, observability, and synthetic test set generation directly into your IDE for free with Galileo's new MCP server
An MCP server to help AI assistants to answer questions and generate AccelByte Extend SDK code more effectively .
MCP server for AI Diagram Maker — generate beautiful software engineering diagrams directly inside Cursor, Claude Desktop, Claude Code, or any MCP-compatible AI agent
ALAPI MCP Tools,Call hundreds of API interfaces via MCP
AI-powered SVG animation generator that transforms static files into animated SVG components using the Allyson platform
MCP server that gives AI assistants on-demand access to 1,500+ amCharts docs, ~300 code examples, and 1000+ class API references.
APIMatic MCP Server is used to validate OpenAPI specifications using APIMatic. The server processes OpenAPI files and returns validation summaries by leveraging APIMatic’s API.
One shared context layer for AI agents and humans — live API specs, DB schemas, and versioned contracts across repos so every agent and teammate works from the same source of truth.
Build and deploy full-stack Next.js apps with 98 tools for React, AWS, and MongoDB
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.





