What can you do with this server?

The Devpipe MCP Server enables AI assistants to comprehensively manage devpipe, a local pipeline runner, through natural language commands. **Configuration Management & Creation:** * Parse, list, and analyze tasks from configurations with execution statistics and history * Validate configuration files for syntax and structure errors * Generate task configurations from templates for various technologies (Go, Python, Node.js, TypeScript, Rust, Docker) * Create complete `config.toml` files from scratch with auto-detected tasks * Configure metrics (JUnit/SARIF) with proper `outputType`/`outputPath` guidance * Create organizational phase headers for logical task grouping **Pipeline Execution & Control:** * Run pipelines with full flag control: `only`/`skip`/`since` (git-based) task selection, `dryRun`, `fast` mode, `failFast`, `fixType` (auto-fix/helper/no-fix), and UI modes (basic/full/dashboard) * Generate CI/CD configurations for GitHub Actions and GitLab CI from devpipe setups **Analysis & Optimization:** * Access run results, metrics (JUnit/SARIF), logs, and aggregated statistics * Auto-detect technologies and suggest missing tasks based on project analysis * Calculate pipeline health scores with trend analysis, failure rates, and performance metrics * Compare pipeline runs to identify changes in failures and performance * Predict task failures based on changed files and historical patterns with risk scores * Suggest pipeline optimizations for improved speed and efficiency * Analyze watchpaths to determine which tasks run based on file changes **Debugging & Troubleshooting:** * Debug task failures using logs and run results analysis * Review security findings from SARIF reports with recommendations * Identify recent failures, error patterns, flaky tasks, and performance regressions * Correlate failures with recent commits and file changes **Resource Access:** * Check devpipe installation status and version information * Access documentation (configuration, examples, CLI reference, features, safety checks) * Retrieve schemas, templates, release notes, and local run data * View git status, changed files, historical task performance, and aggregated metrics * Use pre-configured prompts for common workflows like debugging failures, creating tasks, and security reviews

Which integrations are available for this server?

Enables AI assistants to analyze projects and generate devpipe task configurations for [Docker](/mcp/servers/integrations/docker)-based workflows, including auto-detection of Docker technology in project directories. Allows generation of devpipe task configurations for [ESLint](/mcp/servers/integrations/eslint), enabling AI assistants to help set up JavaScript/TypeScript linting tasks in development pipelines. Supports [Git](/mcp/servers/integrations/git)-based change detection for running devpipe pipelines with the --since flag, enabling targeted task execution based on Git references. Generates [GitHub Actions](/mcp/servers/integrations/github-actions) workflow configurations from devpipe pipelines, automating CI/CD setup with devpipe integration including artifact uploads and result tracking. Generates [GitLab](/mcp/servers/integrations/gitlab) CI configuration files from devpipe pipelines, enabling automated CI/CD workflow creation based on existing devpipe task definitions. Provides task template generation for [Node.js](/mcp/servers/integrations/node-dot-js) projects including linting, testing, and building tasks, with automatic technology detection and configuration suggestions. Offers task template generation for [Python](/mcp/servers/integrations/python) projects covering formatting, linting, type checking, and unit testing, with auto-detection capabilities for Python-based projects. Enables generation of devpipe task configurations for [Rust](/mcp/servers/integrations/rust) projects, allowing AI assistants to suggest and create Rust-specific development pipeline tasks. Provides task template generation for [TypeScript](/mcp/servers/integrations/typescript) type checking and enables AI assistants to create TypeScript-specific devpipe task configurations.

The Devpipe MCP Server enables AI assistants to comprehensively manage devpipe, a local pipeline runner, through natural language commands.

Configuration Management & Creation:

Parse, list, and analyze tasks from configurations with execution statistics and history
Validate configuration files for syntax and structure errors
Generate task configurations from templates for various technologies (Go, Python, Node.js, TypeScript, Rust, Docker)
Create complete config.toml files from scratch with auto-detected tasks
Configure metrics (JUnit/SARIF) with proper outputType/outputPath guidance
Create organizational phase headers for logical task grouping

Pipeline Execution & Control:

Run pipelines with full flag control: only/skip/since (git-based) task selection, dryRun, fast mode, failFast, fixType (auto-fix/helper/no-fix), and UI modes (basic/full/dashboard)
Generate CI/CD configurations for GitHub Actions and GitLab CI from devpipe setups

Analysis & Optimization:

Access run results, metrics (JUnit/SARIF), logs, and aggregated statistics
Auto-detect technologies and suggest missing tasks based on project analysis
Calculate pipeline health scores with trend analysis, failure rates, and performance metrics
Compare pipeline runs to identify changes in failures and performance
Predict task failures based on changed files and historical patterns with risk scores
Suggest pipeline optimizations for improved speed and efficiency
Analyze watchpaths to determine which tasks run based on file changes

Debugging & Troubleshooting:

Debug task failures using logs and run results analysis
Review security findings from SARIF reports with recommendations
Identify recent failures, error patterns, flaky tasks, and performance regressions
Correlate failures with recent commits and file changes

Resource Access:

Check devpipe installation status and version information
Access documentation (configuration, examples, CLI reference, features, safety checks)
Retrieve schemas, templates, release notes, and local run data
View git status, changed files, historical task performance, and aggregated metrics
Use pre-configured prompts for common workflows like debugging failures, creating tasks, and security reviews

Devpipe MCP Server

A Model Context Protocol (MCP) server that enables AI assistants to interact with devpipe - a fast, local pipeline runner for development workflows.

Features

This MCP server provides AI assistants with the ability to:

📋 List and analyze tasks from devpipe configurations (with verbose stats)
🚀 Run pipelines with full control over execution flags
✅ Validate configurations before running
📊 Access run results and metrics (JUnit, SARIF)
🔍 Debug failures by reading task logs
💡 Suggest optimizations for pipeline configurations
🛡️ Review security findings from SARIF reports
🔧 Auto-detect technologies and suggest missing tasks
⚡ Generate task configurations from templates
📝 Create complete configs from scratch
🔄 Generate CI/CD configs (GitHub Actions, GitLab CI)

Requirements

Node.js 18 or higher
devpipe v0.2.0 or later installed and accessible in PATH
brew install drewkhoury/tap/devpipe
Note: This MCP requires devpipe v0.2.0+ which uses outputType/outputPath fields (renamed from metricsFormat/metricsPath).

Installation

Option 1: Install from npm (recommended)

npm install -g devpipe-mcp

Option 2: Install from source

git clone https://github.com/drewkhoury/devpipe-mcp.git cd devpipe-mcp npm install npm run build npm link

Configuration

Add to your MCP configuration file:

Windsurf/Cascade: ~/.codeium/windsurf/mcp_config.json
Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json

{ "mcpServers": { "devpipe": { "command": "npx", "args": [ "-y", "devpipe-mcp@latest" ] } } }

For Other MCP Clients

The server runs on stdio, so you can connect any MCP client using:

devpipe-mcp

Usage

Once configured, you can interact with devpipe through your AI assistant using natural language. The AI will automatically translate your requests into the appropriate tool calls.

📖 Complete Prompting Guide - Learn all the ways to effectively prompt the MCP server

🎯 How to Prompt

The key is to specify which project you want to work with:

"this project" or "this repo" - Uses your current workspace
Project name - e.g., "the devpipe project", "my go-app"
Absolute path - e.g., "/Users/you/projects/my-app"

List Tasks

"Show me all the tasks in this project" "What tasks are defined in /Users/you/projects/my-app/config.toml?" "List tasks from the devpipe project"

Run Pipeline

"Run devpipe in this project" "Run the pipeline for /Users/you/projects/my-app" "Run only the lint and test tasks in this repo" "Execute devpipe in dry-run mode for the go-app project"

Validate Configuration

"Validate my devpipe config" "Check if config.toml is valid"

Debug Failures

"Why did the lint task fail?" "Show me the logs for the build task" "What went wrong in the last run?"

Analyze and Optimize

"Analyze my pipeline configuration" "Suggest optimizations for my devpipe setup" "How can I make my pipeline faster?"

Create Tasks

"Create a devpipe task for running Go tests" "Help me add a Python linting task" "Generate a task configuration for ESLint"

Bootstrap New Projects

"Create a devpipe config for this project" "Analyze the project at /Users/you/projects/new-app" "What technologies are in this repo?" "Generate a config for /path/to/project"

Working with Multiple Projects

"Analyze /Users/you/projects/project-a" "Run devpipe in /Users/you/projects/project-b" "Compare tasks between this project and /Users/you/projects/other-project"

Pro Tip: You don't need to configure anything special - just tell the AI which project you want to work with in your prompt!

Generate CI/CD

"Generate a GitHub Actions workflow for devpipe" "Create a GitLab CI config from my devpipe setup"

Security Review

"Review the security findings from my last run" "What security issues were found?" "Analyze SARIF results"

MCP Tools

The server provides the following tools:

`list_tasks`

Parse and list all tasks from a config.toml file.

Parameters:

config (optional): Path to config.toml file

Example:

{ "config": "./config.toml" }

`run_pipeline`

Execute devpipe with specified flags.

Parameters:

config (optional): Path to config.toml
only (optional): Array of task IDs to run
skip (optional): Array of task IDs to skip
since (optional): Git reference for change-based runs
fixType (optional): auto, helper, or none
ui (optional): basic or full
dashboard (optional): Show dashboard view
failFast (optional): Stop on first failure
fast (optional): Skip slow tasks
ignoreWatchPaths (optional): Ignore watchPaths and run all tasks
dryRun (optional): Show what would run
verbose (optional): Verbose output
noColor (optional): Disable colors

Example:

{ "only": ["lint", "test"], "fast": true, "failFast": true, "ignoreWatchPaths": true }

`validate_config`

Validate devpipe configuration files.

Parameters:

configs (optional): Array of config file paths

Example:

{ "configs": ["config.toml", "config.prod.toml"] }

`get_last_run`

Get results from the most recent pipeline run.

Parameters:

config (optional): Path to config.toml

`view_run_logs`

Read logs from a specific task or the entire pipeline.

Parameters:

taskId (optional): Task ID to view logs for
config (optional): Path to config.toml

Example:

{ "taskId": "lint" }

`parse_metrics`

Parse JUnit or SARIF metrics files.

Parameters:

metricsPath (required): Path to metrics file
format (required): junit or sarif

Example:

{ "metricsPath": ".devpipe/runs/latest/metrics.sarif", "format": "sarif" }

`get_dashboard_data`

Extract aggregated data from summary.json.

Parameters:

config (optional): Path to config.toml

`check_devpipe`

Check if devpipe is installed and get version info.

`list_tasks_verbose`

List tasks using devpipe list --verbose command with execution statistics.

Parameters:

config (optional): Path to config.toml file

Example:

{ "config": "./config.toml" }

Output: Shows task table with average execution times and statistics.

`analyze_project`

Analyze project directory to detect technologies and suggest missing tasks.

Parameters:

projectPath (optional): Path to project directory (defaults to current)

Example:

{ "projectPath": "/path/to/project" }

Output:

{ "projectPath": "/path/to/project", "detectedTechnologies": ["Go", "Docker"], "suggestedTasks": [ { "technology": "Go", "taskType": "check-format", "reason": "go fmt for formatting" }, { "technology": "Go", "taskType": "check-lint", "reason": "golangci-lint for linting" } ], "summary": "Found 2 technologies with 5 suggested tasks" }

`generate_task`

Generate task configuration from template for a specific technology or phase header.

Parameters:

technology (required): Technology name (e.g., "Go", "Python", "Node.js", "TypeScript", "Rust") or "phase" for phase headers
taskType (required): Task type (e.g., "check-format", "check-lint", "test-unit", "build") or phase name
taskId (optional): Custom task ID for regular tasks, or description for phase headers

Example (Regular Task):

{ "technology": "Go", "taskType": "check-lint", "taskId": "golangci-lint" }

Output:

[tasks.golangci-lint] name = "Golang CI Lint" desc = "Runs comprehensive linting on Go code" type = "check" command = "golangci-lint run" fixType = "auto" fixCommand = "golangci-lint run --fix"

Example (Phase Header):

{ "technology": "phase", "taskType": "Validation", "taskId": "Static analysis and tests" }

Output:

[tasks.phase-validation] name = "Validation" desc = "Static analysis and tests"

Note: Phase headers have no required fields - they're organizational markers. Common practice is to include name or desc (or both), but neither is strictly required.

Supported Technologies:

Go: check-format, check-lint, check-static, test-unit, build
Python: check-format, check-lint, check-types, test-unit
Node.js: check-lint, test-unit, build
TypeScript: check-types
phase: Creates phase headers (organizational markers, no command/type)

`create_config`

Create a complete config.toml file from scratch with auto-detected tasks.

Parameters:

projectPath (optional): Path to project directory (defaults to current)
includeDefaults (optional): Include [defaults] section (default: true)
autoDetect (optional): Auto-detect technologies and generate tasks (default: true)

Example:

{ "projectPath": "/path/to/project", "includeDefaults": true, "autoDetect": true }

Output: Complete config.toml with:

Defaults section (outputRoot, fastThreshold=300s, animationRefreshMs=500ms, git settings)
Task defaults (enabled, workdir)
Auto-detected tasks organized by phase
Ready-to-use TOML configuration compatible with devpipe v0.1.0+

Use Case: Bootstrap a new project with devpipe configuration.

Note: Generated configs use devpipe v0.1.0 defaults (fastThreshold=300s, not 5000ms).

`get_pipeline_health`

Calculate overall pipeline health score with trend analysis, failure rates, and performance metrics. Returns health score (0-100), issues, warnings, and recommendations.

`compare_runs`

Compare two pipeline runs to identify changes in failures, performance, and metrics.

Parameters:

run1 (required): First run ID (e.g., 2024-12-07_20-00-00) or latest
run2 (required): Second run ID or previous

Returns: New failures, fixed tasks, performance changes, and detailed task comparisons.

`predict_impact`

Predict which tasks are likely to fail based on changed files and historical patterns.

Returns: Risk scores per task, recommended tasks to run, and suggested devpipe command.

Risk scoring:

WatchPaths matching (40 points)
Historical failure correlation (30 points)
Recent failure rate (30 points)

`generate_ci_config`

Generate CI/CD configuration file (GitHub Actions or GitLab CI) from devpipe config.

Parameters:

config (optional): Path to config.toml file
platform (required): github or gitlab

Example:

{ "config": "./config.toml", "platform": "github" }

Output (GitHub Actions):

name: CI Pipeline on: push: branches: [ main, develop ] pull_request: branches: [ main ] jobs: devpipe: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - name: Install devpipe run: | curl -L https://github.com/drewkhoury/devpipe/releases/latest/download/devpipe-linux-amd64 -o devpipe chmod +x devpipe sudo mv devpipe /usr/local/bin/ - name: Run devpipe run: devpipe --fail-fast - name: Upload results if: always() uses: actions/upload-artifact@v4 with: name: devpipe-results path: .devpipe/

MCP Resources

The server exposes these resources:

devpipe://config - Current config.toml contents
devpipe://tasks - All task definitions
devpipe://last-run - Most recent run results
devpipe://summary - Aggregated pipeline summary
devpipe://schema - JSON Schema for config.toml validation (fetched from official devpipe repo)
devpipe://template-dashboard - HTML template for dashboard reports (fetched from devpipe source)
devpipe://template-ide - HTML template for IDE-optimized views (fetched from devpipe source)
devpipe://releases-latest - Latest devpipe release notes (from GitHub releases)
devpipe://releases-all - Complete release history (from GitHub releases)
devpipe://readme - Complete devpipe documentation (from GitHub)
devpipe://docs-configuration - Official configuration guide (from GitHub)
devpipe://docs-examples - Example config.toml with all options (from GitHub)
devpipe://docs-cli-reference - CLI commands and flags reference (from GitHub)
devpipe://docs-config-validation - Configuration validation rules (from GitHub)
devpipe://docs-features - Complete features guide (from GitHub)
devpipe://docs-project-root - Project root configuration (from GitHub)
devpipe://docs-safety-checks - Safety checks documentation (from GitHub)
devpipe://version-info - Installed devpipe version and capabilities (from local binary)
devpipe://available-commands - All CLI commands and flags (from local binary)
devpipe://git-status - Current git repository status (from local git)
devpipe://changed-files - Files changed based on git mode (from local git)
devpipe://task-history - Historical task performance across all runs (from local runs)
devpipe://metrics-summary - Aggregated test and security metrics (from local runs)
devpipe://watchpaths-analysis - Analyze which tasks will run based on watchPaths (from local config + git)
devpipe://recent-failures - Recent task failures with error details and patterns (from local runs)
devpipe://flakiness-report - Flaky task detection with pass/fail patterns (from local runs)
devpipe://performance-regressions - Tasks that have gotten slower over time (from local runs)
devpipe://change-correlation - Correlate failures with recent commits and file changes (from local git + runs)

MCP Prompts

Pre-configured prompts for common workflows:

`mcp-info`

Get information about this MCP server version and devpipe compatibility. Shows supported field names, run structure, and upgrade guidance.

`analyze-config`

Analyze the devpipe configuration and suggest improvements.

`debug-failure`

Help debug why a specific task failed.

Arguments:

taskId (required): The task that failed

`optimize-pipeline`

Suggest optimizations for the pipeline.

`create-task`

Help create a new task for a technology.

Arguments:

technology (required): Technology name (e.g., "Go", "Python")
taskType (optional): check, build, or test

`security-review`

Review SARIF security findings and provide recommendations.

`configure-metrics`

Help configure JUnit, SARIF, or artifact metrics for a task. Provides guidance on proper metricsFormat and metricsPath configuration.

Examples

See EXAMPLES.md for detailed usage examples and workflows.

Quick Example

User: "Run my devpipe pipeline with fast mode" Assistant: *Uses run_pipeline tool with { "fast": true }* Result: Pipeline executes, skipping slow tasks

Development

Building from Source

git clone https://github.com/drewkhoury/devpipe-mcp.git cd devpipe-mcp npm install npm run build

Project Structure

devpipe-mcp/ ├── src/ │ ├── index.ts # Main MCP server │ ├── types.ts # Type definitions │ └── utils.ts # Utility functions ├── examples/ # Example configs ├── dist/ # Compiled output └── README.md

Watch Mode

npm run watch

Troubleshooting

devpipe not found

If you get "devpipe not found" errors:

# Install devpipe brew install drewkhoury/tap/devpipe # Verify installation devpipe --version

Config file not found

The MCP server searches for config.toml in:

Current directory
Parent directories (up to root)

You can also specify the config path explicitly in tool calls.

Permission errors

Ensure the MCP server has permission to:

Read config files
Execute devpipe commands
Access the .devpipe output directory

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

License

MIT License - see LICENSE file for details.

devpipe - The pipeline runner this MCP server integrates with
Model Context Protocol - The protocol specification

Support

Issues: GitHub Issues
Discussions: GitHub Discussions
devpipe: devpipe GitHub

Changelog

See CHANGELOG.md for version history and changes.

One-click Deploy

security – no known vulnerabilities

license - permissive license

quality - confirmed to work

How are these scores calculated?

Resources

Need Help?

Report Issue

Related Servers

Tools

View all tools

Devpipe MCP Server

Features

Requirements

Installation

Option 1: Install from npm (recommended)

Option 2: Install from source

Configuration

For Other MCP Clients

Usage

🎯 How to Prompt

List Tasks

Run Pipeline

Validate Configuration

Debug Failures

Analyze and Optimize

Create Tasks

Bootstrap New Projects

Working with Multiple Projects

Generate CI/CD

Security Review

MCP Tools

list_tasks

run_pipeline

validate_config

get_last_run

view_run_logs

parse_metrics

get_dashboard_data

check_devpipe

list_tasks_verbose

analyze_project

generate_task

create_config

get_pipeline_health

compare_runs

predict_impact

generate_ci_config

MCP Resources

MCP Prompts

mcp-info

analyze-config

debug-failure

optimize-pipeline

create-task

security-review

configure-metrics

Examples

Quick Example

Development

Building from Source

Project Structure

Watch Mode

Troubleshooting

devpipe not found

Config file not found

Permission errors

Contributing

License

Related Projects

Support

Changelog

Resources

Tools

New MCP Servers

Latest Blog Posts

MCP directory API

`list_tasks`

`run_pipeline`

`validate_config`

`get_last_run`

`view_run_logs`

`parse_metrics`

`get_dashboard_data`

`check_devpipe`

`list_tasks_verbose`

`analyze_project`

`generate_task`

`create_config`

`get_pipeline_health`

`compare_runs`

`predict_impact`

`generate_ci_config`

`mcp-info`

`analyze-config`

`debug-failure`

`optimize-pipeline`

`create-task`

`security-review`

`configure-metrics`