Your local coding-agent HQ — four agents, one local LLM, ten MCP servers, zero cloud dependencies.
Most AI and media services work still happens through a UI a human drives. Ashlr Workbench MCP server moves it into the conversation instead. Your local coding-agent HQ — four agents, one local LLM, ten MCP servers, zero cloud dependencies.
The server publishes 1 tool. What each one is for:
Scenario — Best agentConfiguration is passed through the environment: GITHUB_TOKEN, XAI_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
qwen/qwen3-coder-30b loaded — primary LLM - Bun ≥ 1.1 — for ashlr-plugin MCP servers and ashlrcode - Python 3.12+ — for Aider - Node ≥ 20 / npm — for npm install -g ashlrcode - ~32 GB free RAM (Qwen3-Coder-30B in 4-bit needs ~24 GB live) - ~30 GB free diskThe server ships on npm as ashlrcode, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
This sits in the AI and media services group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Ashlr Workbench's toolset — Scenario — is a fair guide to whether it matches your workflow. It is maintained by ashlrai; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Scenario | Best agent |
{
"mcpServers": {
"ashlr-workbench": {
"command": "npx",
"args": ["-y", "ashlrcode"],
"env": {
"GITHUB_TOKEN": "your-value",
"XAI_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
qwen/qwen3-coder-30b loaded — primary LLM - Bun ≥ 1.1 — for ashlr-plugin MCP servers and ashlrcode - Python 3.12+ — for Aider - Node ≥ 20 / npm — for npm install -g ashlrcode - ~32 GB free RAM (Qwen3-Coder-30B in 4-bit needs ~24 GB live) - ~30 GB free disk| Variable | Description | Required |
|---|---|---|
| GITHUB_TOKEN | Credential the server authenticates with. | Yes |
| XAI_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.