prime-intellect-mcp
# prime-intellect-mcp
> Let Claude Code rent, drive, and terminate Prime Intellect GPU pods on its own — with hard spend caps you control.
[](https://pypi.org/project/prime-intellect-mcp/)
[](https://pypi.org/project/prime-intellect-mcp/)
[](LICENSE)
[](https://github.com/kvrancic/prime-intellect-mcp/actions)
[](https://modelcontextprotocol.io)
---
## What this is
An [MCP](https://modelcontextprotocol.io) server that connects [Claude Code](https://docs.claude.com/en/docs/claude-code) (or any MCP client) to your [Prime Intellect](https://primeintellect.ai) account. With it, the agent can:
- 🔍 **Find** the cheapest GPU pod that matches your requirements
- 💸 **Quote** a price *before* committing money
- 🛒 **Provision** the pod (only after you say `confirm=True`)
- 🖥️ **SSH** into it (the connection string is handed to the agent's own `Bash` tool)
- 🛑 **Terminate** it when work is done — and warn loudly if you forget
Built for one workflow: telling Claude *"rent the cheapest H100, run my training script, then kill it"* and not waking up to a $400 bill.
---
## Install in 60 seconds
You only need this much to start renting GPUs through Claude Code:
### 1. Get a Prime Intellect API key
[**Click here to generate one**](https://app.primeintellect.ai/dashboard/api-keys) → set permissions:
| Scope | Level |
|---|---|
| **Instances** | Read and write |
| **Availability** | Read only |
| **Billing** | Read only |
| **SSH Keys** | Read only |
Copy the key — it starts with `pit_…`.
### 2. Add the server to Claude Code
Open `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS) or your project's `.mcp.json`, and paste:
```json
{
"mcpServers": {
"prime-intellect": {
"command": "uvx",
"args": ["prime-intellect-mcp"],
"env": {
"PRIME_API_KEY": "pit_PASTE_YOURS_HERE",
"PRIME_MAX_HOURLY_USD": "5",
"PRIME_MAX_TOTAL_USD": "40"
}
}
}
}
```
That's it. Restart Claude Code and ask: *"What GPUs are available right now under $1/hr?"*
> Don't have `uvx`? Install it with `curl -LsSf https://astral.sh/uv/install.sh | sh` (or `brew install uv`). It's a one-liner installer for the `uv` package manager and you'll never have to manage a virtualenv again.
---
## ✨ Add SSH (optional, +2 min) — needed for Claude to actually run code on the pod
The server above can already provision/inspect/terminate pods. But to have Claude Code SSH into a running pod and execute commands on it, Prime Intellect needs to know your machine's public SSH key.
### 3. Find or generate an SSH key on your machine
```bash
ls ~/.ssh/*.pub # if you have id_ed25519.pub or similar, you're set
# otherwise:
ssh-keygen -t ed25519 -C "you@example.com" # press Enter through the prompts
```
### 4. Register the public key with Prime Intellect
```bash
cat ~/.ssh/id_ed25519.pub # or whichever .pub file you have
```
Copy the output (one line starting with `ssh-ed25519 …`), then paste it into the **Add SSH key** form at [app.primeintellect.ai/dashboard/ssh-keys](https://app.primeintellect.ai/dashboard/ssh-keys).
That's it. Future pods will have your public key in `authorized_keys`, and Claude Code's `Bash` tool can SSH straight in:
```
ssh ubuntu@<pod-ip-from-pod_status> "nvidia-smi"
```
> **Coming in v0.2:** a `register_ssh_key` MCP tool that does step 4 from inside Claude (no browser visit). See [the issue tracker](https://github.com/kvrancic/prime-intellect-mcp/issues) to follow along.
---
## What Claude can now do (the 9 tools)
| Tool | Use case |
|---|---|
| `list_gpu_types` | "What GPU types does Prime Intellect offer?" |
| `list_availability` | "Show me 1×H100 pods available under $3/hr." |
| `get_wallet_balance` | "How much credit do I have left?" |
| `pod_quote` | "Quote me a 1×A100 with 200GB disk." (no charge) |
| `pod_create` | "Provision the pod from that quote." (requires `confirm=True`) |
| `pod_list` | "Show me my running pods." |
| `pod_status` | "Is pod X ready? Wait until it has SSH info." |
| `pod_terminate` | "Kill pod X." (requires `confirm=True`) |
| `pod_check_runaway` | "Did I forget to terminate anything?" |
---
## Safety: nothing provisions silently
Three layers, in order:
1. **Quote first.** `pod_quote` returns a price + a 60-second token. No side effects. The dollar amount is now in the agent's context.
2. **Explicit confirm.** `pod_create` (and `pod_terminate`) requires `confirm=True`. Without it, you get a dry-run preview.
3. **Hard env-var caps.** `PRIME_MAX_HOURLY_USD` blocks any pod above the rate. `PRIME_MAX_TOTAL_USD` blocks any (rate × max_lifetime_hours) above the budget. Wallet balance is also enforced. **None of these caps can be overridden by tool arguments** — they're read at every call.
Defaults: `PRIME_MAX_HOURLY_USD=5`, `PRIME_MAX_TOTAL_USD=40`. Set them in your config's `env` block.
Every `pod_create` / `pod_terminate` is appended as JSON to `~/.prime-intellect-mcp/audit.log`, so you have a complete history of what the agent did with your money.
---
## Example prompts (paste these into Claude Code)
```
List the cheapest 1×H100 pods available right now. Show me the top 3 by hourly price.
```
```
Quote a 1×A100 80GB with 100GB disk, 8 vCPU, 64GB RAM. Don't provision yet —
just show me what it would cost.
```
```
I need to fine-tune a 7B model overnight. Find the cheapest 1×H100 with 200GB
disk, max $40 total budget, max 12 hours. Provision it, give me the SSH command,
and remind me to terminate when I'm done.
```
```
Check if I have any running pods I forgot about and show me their hourly cost.
```
```
Terminate pod abc123. Confirm before doing it.
```
---
## Troubleshooting
<details>
<summary><b><code>PRIME_API_KEY is not set</code></b></summary>
Either your Claude Code config didn't pick up the `env` block, or you typed `PRIME_API_KEY` as a different variable. Verify with:
```
$ env | grep PRIME
```
inside the same shell that launches Claude Code, or paste the key directly into the JSON `env` block (instead of using `${PRIME_API_KEY}`).
</details>
<details>
<summary><b><code>Hourly rate $X/hr exceeds PRIME_MAX_HOURLY_USD cap</code></b></summary>
The agent picked a pod above your hard cap. Either:
- Pick a cheaper GPU (`list_availability` with a region filter often surfaces cheaper community-priced rows), or
- Raise `PRIME_MAX_HOURLY_USD` in your config and restart Claude Code.
</details>
<details>
<summary><b><code>Quote token expired</code></b></summary>
Quotes live 60 seconds; the agent waited too long between `pod_quote` and `pod_create`. Just call `pod_quote` again — it's a no-op cost-wise.
</details>
<details>
<summary><b>Pod is "ACTIVE" but <code>ssh_connection</code> is null</b></summary>
Provisioning isn't fully done. The pod is alive but still running its install script. Call `pod_status(pod_id, wait_for_ssh=True)` and it will block (polling every 5s) until SSH comes up.
</details>
<details>
<summary><b><code>ssh: Permission denied (publickey)</code></b></summary>
You haven't told Prime Intellect about your public key (or the pod was provisioned before you registered it). Fix:
1. Verify your pubkey is registered at [app.primeintellect.ai/dashboard/ssh-keys](https://app.primeintellect.ai/dashboard/ssh-keys).
2. **Re-provision** — the pod's `authorized_keys` is set at create time, so existing pods won't pick up keys you registered after.
3. If your private key has a passphrase, run `ssh-add --apple-use-keychain ~/.ssh/your_key` once on macOS so the agent unlocks it silently from now on.
</details>
<details>
<summary><b>Wallet balance is empty / <code>PaymentRequiredError</code></b></summary>
Top up at [app.primeintellect.ai/wallet](https://app.primeintellect.ai/wallet) and try again.
</details>
---
## Why another one?
There's a [`prime-mcp-server` 0.1.2](https://pypi.org/project/prime-mcp-server/) on PyPI. It's a thin proof-of-concept; this isn't a fork. Differences for unattended overnight use:
| | `prime-intellect-mcp` | `prime-mcp-server` 0.1.2 |
|---|---|---|
| Two-step quote → confirm | ✅ | ❌ |
| Env-var hard spend caps | ✅ | ❌ |
| Wallet pre-check | ✅ | ❌ |
| Runaway-pod detection | ✅ | ❌ |
| SSH handoff to agent | ✅ | ❌ |
| Tests | 32 unit + opt-in live | None |
---
## Local development
```bash
git clone https://github.com/kvrancic/prime-intellect-mcp
cd prime-intellect-mcp
uv sync
uv run pytest -m "not live" # 32 fast tests, no network, no spend
uv run ruff check .
uv run mypy src
```
Live smoke test (provisions cheapest available GPU, runs `nvidia-smi`, terminates; ~$0.05 spend):
```bash
PRIME_API_KEY=pit_... PRIME_LIVE_TEST=1 PRIME_LIVE_MAX_HOURLY=0.60 \
PRIME_MAX_HOURLY_USD=0.60 PRIME_MAX_TOTAL_USD=2.00 \
uv run pytest tests/test_smoke_live.py -v -s
```
---
## Roadmap
- **v0.2** — `register_ssh_key` MCP tool (kill the dashboard step), Sandboxes (`prime-sandboxes` SDK), Environments Hub
- **v0.3** — Optional auto-terminate daemon (server-side enforcement of `max_lifetime_hours`); cost telemetry
- **v1.0+** — Hosted/OAuth deployment when Prime Intellect ships OAuth; submission to Anthropic connector directory
---
## Acknowledgements
- [Prime Intellect](https://primeintellect.ai) for the [`prime` Python SDK](https://github.com/PrimeIntellect-ai/prime) that does 90% of the work
- MIT 6.8610 (Advanced NLP) for the Prime Intellect credits that made testing this possible
- [Anthropic](https://anthropic.com) for [MCP](https://modelcontextprotocol.io)
- [FastMCP](https://gofastmcp.com) for the framework
## License
MIT — see [LICENSE](LICENSE).
## Contributing
Issues and PRs welcome. Please run `uv run pytest -m "not live"` and `uv run ruff check .` before submitting.
TDQS
Scored across 9 tools
Each tool has a unique and clearly distinct purpose, from wallet balance and GPU availability listing to pod creation, quoting, and termination. There is no overlap that could cause an agent to select the wrong tool.
Tool names follow a consistent pattern: utility functions use verb_noun (e.g., get_wallet_balance, list_availability) and pod operations all start with pod_ (e.g., pod_create, pod_terminate). The naming is predictable and easily understood.
With 9 tools covering wallet, GPU types, availability, pod lifecycle (create, list, status, quote, terminate), and runaway monitoring, the count is well-scoped for the server's purpose. Each tool earns its place with no redundancy.
The tool surface covers the full lifecycle of GPU pod management: discovering availability, quoting, creating, monitoring status, listing, terminating, and checking for runaway pods. The inclusion of wallet balance and wait-for-SSH functionality addresses common operational needs.