About Fireworks AI MCP by usefulapi
Fireworks AI MCP by usefulapi is a hosted MCP server for Fireworks AI users to inspect models, deployments, datasets, and fine-tuning jobs from MCP clients. It also supports dataset creation and deployment deletion.
Key features
- 01Inspect account and model details
- 02List deployments and deployed models
- 03List and inspect datasets
- 04View fine-tuning and batch inference jobs
- 05Create datasets or delete deployments
Use cases
- 01Review models in a Fireworks AI account
- 02Check deployment and deployed model details
- 03Browse datasets and fine-tuning jobs
- 04Create datasets or remove deployments
MCP support
It exposes Fireworks AI inspection and management tools to MCP clients through a remote server. On first connection, users submit a Fireworks API key, which is validated and stored per user.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://fireworks.usefulapi.io/mcpclaude mcp add --transport http io-usefulapi-fireworks https://fireworks.usefulapi.io/mcp{"mcpServers":{"io-usefulapi-fireworks":{"type":"http","url":"https://fireworks.usefulapi.io/mcp"}}}Open in Cursor{"servers":{"io-usefulapi-fireworks":{"type":"http","url":"https://fireworks.usefulapi.io/mcp"}}}Open in VS Code{"mcpServers":{"io-usefulapi-fireworks":{"type":"http","url":"https://fireworks.usefulapi.io/mcp"}}}{"mcpServers":{"io-usefulapi-fireworks":{"serverUrl":"https://fireworks.usefulapi.io/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
14| Parameter | Type | Required | Description |
|---|---|---|---|
| account_id | string | No | Fireworks account id. Overrides FIREWORKS_ACCOUNT_ID for this call. |
Details
From the project READMEFireworks AI MCP by usefulapi
Inspect Fireworks AI models, deployments, datasets and fine-tuning jobs from Claude, Cursor, or any MCP client. Hosted, no local install — connect with your Fireworks API key.
Live endpoint: https://fireworks.usefulapi.io/mcp · Homepage: https://usefulapi.io/fireworks
Connect
- Claude (claude.ai, Desktop): open Customize → Connectors, click + Add → Add custom connector, and paste
https://fireworks.usefulapi.io/mcp. - Claude Code:
claude mcp add --transport http fireworks https://fireworks.usefulapi.io/mcp, then run/mcpto log in. - VS Code: Add to VS Code.
- Cursor and other clients: add the URL as a remote MCP server:
{
"mcpServers": {
"fireworks": {
"url": "https://fireworks.usefulapi.io/mcp"
}
}
}
Add only the URL. Do not add an Authorization header or an API key to the client config: the server signs you in with OAuth, and the login page asks for your Fireworks AI credentials.
Step-by-step setup, where to find your credentials, and FAQ: https://usefulapi.io/fireworks/
On first connect you'll paste your Fireworks API key. It's validated, stored per-user, and scoped to you.
Tools
| Tool | Type | What it does |
|---|---|---|
fireworks_get_account | read | Get account |
fireworks_list_models | read | List models |
fireworks_get_model | read | Get model |
fireworks_list_deployments | read | List deployments |
fireworks_get_deployment | read | Get deployment |
fireworks_list_deployed_models | read | List deployed models |
fireworks_list_datasets | read | List datasets |
fireworks_get_dataset | read | Get dataset |
fireworks_list_fine_tuning_jobs | read | List fine-tuning jobs |
fireworks_get_fine_tuning_job | read | Get fine-tuning job |
fireworks_list_batch_inference_jobs | read | List batch inference jobs |
fireworks_list_users | read | List users |
fireworks_create_dataset | write | Create dataset |
fireworks_delete_deployment | write | Delete deployment |
fireworks_usage_status | meta | Usage status (free-tier meter) |
fireworks_request_feature | meta | Request a missing feature |
fireworks_upgrade | meta | Upgrade to Pro (unlimited*) |
fireworks_cancel_subscription | meta | Cancel the Pro subscription |
read tools are read-only; write tools mutate data (clients should confirm them); meta tools report usage, manage your subscription or send a feature request.
Pricing
| Plan | Price | Limit |
|---|---|---|
| Free | $0 | 50 tool calls / month |
| Pro | $9/mo or $90/yr (2 months free) | Unlimited* |
*Pro has a fair use limit of 10,000 tool calls a month on this server. For more, write to [email protected].
Pro covers this server only. Subscribe with fireworks_upgrade (it returns a Stripe Checkout link). Cancel any time with fireworks_cancel_subscription: Pro continues to the end of the paid period, with no refund for the current period, and running fireworks_upgrade before then undoes the cancel. Or write to [email protected].
License
MIT — see LICENSE. Documentation only; the server is hosted.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.