Chat triggers the work. Magpie does the rest. From task description to pull request, fully automated with AI agents, CI validation, and intelligent blueprint execution.
Magpie orchestrates a complete autonomous coding pipeline from a single chat message
1
Trigger from chat
Mention @magpie in Discord, Teams, or run a CLI command with your task description. Magpie reads the full thread context to understand requirements.
2
Intelligent classification
The pipeline analyzes your task and classifies it as Simple (docs/typos), Standard (features), or BugFix (fixes). Each complexity level triggers a different blueprint optimized for that work.
Simple → single-shot agent callStandard → TDD: plan → tests → implementBugFix → Diagnostic: investigate → regression test → fix
3
Agent execution with blueprints
Magpie uses a two-tier LLM architecture: Claude CLI for text generation (branch names, commit messages) and Goose agent for coding work. The blueprint engine orchestrates deterministic Shell steps and AI Agent steps in sequence.
After the agent completes coding, Magpie runs your configured lint and test commands. If CI fails, the fix blueprint receives the error output and attempts repairs (up to 2 rounds by default).
// Configured via environment variablesMAGPIE_LINT_CMD="cargo clippy"MAGPIE_TEST_CMD="cargo test"MAGPIE_MAX_CI_ROUNDS="2"
5
Commit, push, and PR
Once tests pass, Magpie generates a commit message, pushes to a new branch with collision handling, and opens a pull request via gh CLI. The result is posted back to your chat thread.
Magpie integrates with Plane for issue tracking and Daytona for sandboxed execution. All agent calls are traced to JSONL for observability.
Key features
Built for production autonomous coding workflows
Blueprint engine
Hybrid orchestration with deterministic Shell steps and AI Agent steps. Three built-in blueprints: Simple, TDD, and Diagnostic.
Two-tier LLM
Tier 1 (Claude CLI) for clean text generation. Tier 2 (Goose agent) for multi-turn coding with full tool access.
Multi-platform adapters
Discord bot, Teams webhook, and CLI. All implement the ChatPlatform trait for consistent integration.
Sandbox abstraction
Local execution or remote Daytona sandboxes. Swap implementations via trait without pipeline changes.
Org-scoped repos
Dynamic repo resolution from task messages. One Magpie instance works across multiple repositories in your GitHub org.
CI classification
Docs-only changes skip CI. Built-in test steps in blueprints eliminate redundant CI runs.
Observability
JSONL traces for every agent call. Verbose mode prints streaming events. Debug and audit all LLM interactions.
Git automation
Branch collision handling, conventional commit generation, and PR automation via GitHub CLI.
Architecture at a glance
Magpie is a Rust workspace with four crates
magpie-core
Core library. Pipeline orchestrator, blueprint engine, agent wrapper, git ops, Plane client, repo resolution, tracing. All other crates depend on this.
magpie-cli
CLI binary for running prompts, blueprints, or the full pipeline locally. Thin wrapper around magpie-core.
magpie-discord
Discord bot adapter (Serenity). Triggers pipeline when @magpie is mentioned. Creates a thread per task, archives on completion.
magpie-teams
Microsoft Teams webhook adapter (Axum). Receives Bot Framework events and triggers the pipeline.
Ready to automate your coding workflow?
Get started with Magpie in minutes. Install the CLI, configure your environment, and start issuing tasks from Discord, Teams, or the command line.