Swarmrails MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| SWARMRAILS_API_KEY | No | Set this environment variable for real USDC payments. Each transaction hash on the Base blockchain is used as a single-use API token. Format: myapp:0xYOUR_TX_HASH. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| bittensor_textA | Conversational AI via Bittensor subnet 1 (Text Prompting). Good for general questions, summaries, and chat. Cost: $0.005 per call. |
| bittensor_translateB | Multilingual translation via Bittensor subnet 3 (Machine Translation). Cost: $0.005 per call. |
| bittensor_reasoningA | Advanced reasoning via Bittensor subnet 4 (Targon). Best for complex multi-step problems. Cost: $0.05 per call. |
| bittensor_imageA | Text-to-image synthesis via Bittensor subnet 5. Returns an image URL. Cost: $0.075 per call. |
| bittensor_llmA | Fine-tuned LLM inference via Bittensor subnet 6 (Nous Research). Cost: $0.01 per call. |
| bittensor_forecastA | Financial and crypto time series forecasting via Bittensor subnet 8. Cost: $0.05 per call. |
| bittensor_codeB | Advanced code generation via Bittensor subnet 11. Cost: $0.01 per call. |
| bittensor_dataB | Data analysis and synthesis via Bittensor subnet 13 (Data Universe). Cost: $0.005 per call. |
| bittensor_ttsA | Text-to-speech via Bittensor subnet 16. Returns audio as base64 MP3. Cost: $0.025 per call. |
| bittensor_scrapeA | Web scraping and URL content extraction via Bittensor subnet 21. Cost: $0.01 per call. |
| bittensor_multimodalA | Image + text reasoning via Bittensor subnet 24 (Omega Multimodal). Cost: $0.02 per call. |
| bittensor_videoA | Text-to-video generation via Bittensor subnet 18. Async — polls until ready (up to 3 min). Returns an MP4 URL. Cost: $2.00 per call. |
| bittensor_3dA | Image-to-3D asset generation via Bittensor subnet 29. Requires a source image URL. Async — polls until ready (up to 3 min). Returns a GLB file URL. Cost: $0.75 per call. |
| sharpsignal_predictA | Prediction market intelligence. Submit any yes/no question and get back a structured bull case, bear case, and implied probability from live web search. Powered by Perplexity sonar-reasoning-pro. Cost: $0.25 per call. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 14 tools
Most tools map to distinct modalities (image, video, code, etc.) with clear boundaries. However, `bittensor_text`, `bittensor_llm`, and `bittensor_reasoning` all handle text generation and could be confused without careful reading of their specific subnet specializations. The `sharpsignal_predict` tool is clearly distinct as the only prediction market service.
Thirteen tools follow a consistent `bittensor_<capability>` snake_case pattern that clearly indicates their function and source network. The `sharpsignal_predict` tool breaks this convention, though this is semantically justified as it uses Perplexity rather than Bittensor. All tools use descriptive, action-oriented nouns that align with their outputs.
Fourteen tools appropriately cover the breadth of Bittensor subnet offerings without excessive bloat. Each tool represents a distinct AI service (text, image, video, code, etc.) that earns its place in a comprehensive generative AI gateway. The count balances granularity with usability.
The set provides robust coverage of major generative AI modalities including text, image, video, 3D, audio, and code generation, plus data analysis and prediction markets. Minor gaps exist (e.g., no speech-to-text or image editing), but the surface covers the stated purpose of Bittensor subnet access comprehensively. The addition of prediction market intelligence adds valuable orthogonal functionality.