Branchable LLM history DAG + encrypted context capsules agents can save, restore, and crypto-shred.
Most AI and media services work still happens through a UI a human drives. Forkmind MCP server moves it into the conversation instead. Branchable LLM history DAG + encrypted context capsules agents can save, restore, and crypto-shred.
ForkMind captures every LLM call into a local .forkmind/ directory, visualizes the conversation as a Directed Acyclic Graph (DAG), and lets you branch, diff, and replay from any point in the history. Works with any OpenAI-compatible API, defaulting to free, open-source models via Ollama — also Anthropic, Groq, OpenRouter, Together, vLLM, and LM Studio.
Configuration is passed through the environment: GROQ_API_KEY, ANTHROPIC_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.
The server ships on npm as forkmind, 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. It is maintained by Medhovarsh; 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We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
{
"mcpServers": {
"forkmind": {
"command": "npx",
"args": ["-y", "forkmind"],
"env": {
"GROQ_API_KEY": "your-value",
"ANTHROPIC_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| GROQ_API_KEY | Credential the server authenticates with. | Yes |
| ANTHROPIC_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.