Finsliparn
Integrates with GitHub Copilot CLI to autonomously execute a refinement loop using directive-based instructions until completion.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@FinsliparnImplement a fibonacci function in src/math.ts"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Finsliparn
Swedish: the honer β from finslipa, meaning "to hone", "to fine-tune" or "to put the finishing touches on."
Finsliparn is a Bun-native MCP Server and Claude Code Plugin that transforms single-attempt coding into a multi-attempt, test-validated refinement loop. It adapts the philosophy of Poetiq's ARC-AGI solver to general software development.
π― Core Value Proposition
LLMs often generate code that looks correct but fails in edge cases. Finsliparn solves this by enforcing a Refinement Loop:
Iterate: The LLM implements a solution.
Validate: Finsliparn runs your actual test suite (not just a syntax check).
Feedback: Test failures are fed back to the LLM as structured, actionable directives.
Select: If multiple attempts are made, the best one (highest score, lowest complexity) is selected.
"Test results are the objective truthβnot diffs, not prompts, not opinions."
Related MCP server: Debugging MCP Server
π Architecture
Finsliparn uses a Filesystem-as-IPC architecture to support multiple AI platforms with a single core engine.
graph LR
subgraph "AI Client"
Claude[Claude Code]
Copilot[GitHub Copilot]
end
subgraph "Finsliparn Core"
MCP[MCP Server]
Directive[Directive.md]
Tests[Test Runner]
end
Claude --"Hooks"--> MCP
Copilot --"Agent"--> MCP
MCP --"Writes"--> Directive
Directive --"Reads"--> Claude
Directive --"Reads"--> Copilot
MCP --"Executes"--> Testsdirective.md: The single source of truth. It tells the LLM exactly what to do next (e.g., "Fix failing tests insrc/foo.ts").Git Worktrees: Every iteration runs in an isolated worktree, ensuring your main branch stays clean until a solution is verified.
π Getting Started
Prerequisites
Bun v1.3+
Git
Installation (Development)
# Clone the repository
git clone https://github.com/jgabor/finsliparn.git
cd finsliparn
# Install dependencies
bun install
# Link the plugin (for Claude Code)
# (Coming soon)π Documentation
Technical Specification (v1.0.0): The core architecture and Claude Code integration.
Copilot CLI Support (v2.0.0): Adaptation for GitHub Copilot CLI agents.
Roadmap: Development plan and status.
π Usage
With Claude Code
# Start a refinement session
/finslipa Implement a fibonacci function in src/math.tsFinsliparn will automatically intercept your edits, run tests, and guide you until the tests pass.
With GitHub Copilot CLI
# Start the agent
copilot run --agent finsliparn "Implement a fibonacci function"The agent will autonomously loop through the directive.md instructions until completion.
Author
Jonathan Gabor
This server cannot be deployed
Maintenance
Related MCP Connectors
Writes adversarial test suites for AI-built code. Your agent's test engineer.
Adaptive plan/build/review cycles for AI coding assistants, persisted across sessions.
Generates unit tests for Python code with coverage before/after reports and concrete edge cases.
Proves AI-generated Python does what you asked: lint, types, security, sandbox run, exact fixes.
Related MCP Servers
- AlicenseAqualityBmaintenanceEnforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.2035 npm12MIT
- FlicenseAqualityDmaintenanceEnables LLMs to automatically diagnose coding errors through codebase search, test execution, and live debugger integration (DAP/V8 CDP). Provides a secure, policy-gated environment for investigating failures while preventing destructive operations.9-
- AlicenseNot gradedqualityDmaintenanceEnables AI-powered code review and improvement, including analysis, refactoring suggestions, and automatic test generation, with an optional agentic loop for iterative refinement.MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI models (Claude, ChatGPT, GitHub Copilot) to run and analyze local tests, rerun failures, and orchestrate QA workflows using existing UI and API test frameworks.6 npmMIT