Skein Toolkit MCP Server

Skein Toolkit MCP Server

A local MCP SSE server that proxies Cloudflare Workers AI and provides multi-step task orchestration, integrating with LiteLLM to enable AI-assisted development workflows.

Category
Visit Server

README

Skein Toolkit

A repo-agnostic clone of the AI development toolchain originally built inside Electron-Splines: a Cloudflare Workers AI proxy, a multi-step task orchestrator, and a local agentic MCP server, fronted by a unified LiteLLM proxy.

This repo is the result of the "LLM Tech Stack Standalone Repository" spin-off (see architecture-docs/global/ai-task-queue.md, AT-1116-1139, in the Electron-Splines repo for the full task history and rationale). Further refinement of this agentic system happens here, not in Electron-Splines.

What's in here

Path Purpose
mcp-server/local-mcp.py The core: a local MCP SSE server (port 3100) that also proxies/instruments Cloudflare Workers AI requests at /cfproxy/{account_id}/..., including a multi-step task orchestrator with bounded-ambiguity escalation.
mcp-server/devserver-mcp.py A lighter MCP server variant for a remote GPU devserver.
mcp-server/litellm_config.yaml + litellm.env.example LiteLLM unified proxy config routing local/CF/Groq/DeepSeek/Anthropic/OpenAI models.
mcp-server/run-cline.ps1, resume-orchestrator-run.ps1, toolchain-doctor.ps1, start-litellm.ps1 Launcher/diagnostic scripts for running Cline against this stack on Windows.
cloudflare/README.md Cloudflare Workers AI configuration (env-var only -- no zone/firewall config).
docker-compose.yml, docker-compose.override.yml, docker/ Containerized mcp-server + LiteLLM stack.

Quick start (local, Windows)

  1. Create a Python virtualenv at the repo root and install dependencies:
    python -m venv .venv
    .venv\Scripts\pip install -r mcp-server\requirements.txt
    
  2. Copy mcp-server\litellm.env.example to mcp-server\litellm.env and fill in your API keys (see cloudflare/README.md for the Cloudflare token).
  3. Run mcp-server\toolchain-doctor.ps1 to diagnose and (where possible) auto-start LiteLLM and local-mcp.py.
  4. Run mcp-server\run-cline.ps1 -Task "..." to launch Cline against the configured model.

By default, local-mcp.py operates on the parent of the mcp-server/ directory (i.e. this repo's checkout). Set WORKSPACE_ROOT to point it at a different project checkout instead.

Quick start (Docker)

cp docker/.env.example docker/.env   # fill in API keys
docker compose up --build

This starts mcp-server (port 3100) and litellm (port 4000, dashboard at /ui). By default mcp-server operates on ./workspace -- use docker-compose.override.yml to mount a different project checkout.

Environment variables

Variable Default Purpose
WORKSPACE_ROOT parent of mcp-server/ Project checkout local-mcp.py reads/writes/runs commands in.
CF_API_BASE / CF_API_KEY -- Cloudflare Workers AI proxy target + token. See cloudflare/README.md.
CF_PROXY_OQ_LEDGER_PATH architecture-docs/global/architect-open-questions.md Path (relative to WORKSPACE_ROOT) to an "open questions" ledger the orchestrator appends bounded-ambiguity rows to. If the consuming project has no such ledger, leave the default -- failures to read/write it are logged and degrade to "ambiguity surfaced inline", not a crash.
CF_PROXY_USD_TO_AUD_RATE, CF_PROXY_MONTHLY_BUDGET_AUD, CF_PROXY_DAILY_REVIEW_THRESHOLD_USD 1.42, 100.00, derived CF spend-review accounting (optional).

Status

This is an early-stage clone (Phase 1 of the migration plan in planning_document.md): the toolchain runs standalone, but the orchestrator's "open questions" / "actionable tasks" governance integration (CF_PROXY_OQ_LEDGER_PATH and friends) still assumes an Electron-Splines-style architecture-docs/ layout when enabled. Generalizing that integration into reusable create_open_question / create_actionable_task MCP tools is tracked as AT-1137-1139 in the source repo.

Full mirroring of the consuming project's app/, engine/, and scripts/ directories (AT-1117/1118/1119) has not been done here -- this clone currently contains only the AI-toolchain pieces (MCP server, orchestrator, LiteLLM, Cloudflare/Docker config). If the original AT-1117/1118 scope (mirroring the entire Electron-Splines app and engine source trees into this repo) is still wanted, that is a separate, much larger effort and should be re-scoped with the architect first.

License

Licensed under the Apache License, Version 2.0 -- see LICENSE and NOTICE. This is a deliberate relaxation from the proprietary Electron-Splines source repository's license, applying only to this standalone toolkit: the goal is to let other projects and contributors adopt and extend the MCP server/orchestrator/CF-proxy toolchain, and to make it mergeable into complementary open-source projects (e.g. Odysseus, AGPL-3.0 -- permissively licensed code can be incorporated into an AGPL project).

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured