Newton MCP Gateway
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ATAI_API_KEY | No | Archetype AI API key. Required when NEWTON_BACKEND=api. | |
| NEWTON_BACKEND | Yes | Backend to use. Set to 'mock' for the built-in mock backend (no credentials needed), or 'api' to use the real Newton API. | |
| ATAI_API_ENDPOINT | No | Archetype AI API endpoint, e.g. https://api.u1.archetypeai.app/v0.5. Used with the real Newton backend. |
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 | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| newton_queryB | Ask Newton (text-reasoning model) a natural-language question about physical-world data. Ground it with inline text/JSON events or previously uploaded file_ids. Use system_prompt to force structured JSON output. |
| newton_embed_timeseriesA | Encode a sensor window with the Newton Omega encoder. Input is channel-first: outer list = channels, inner lists = samples. Returns one 768-dim embedding per channel. Leave normalize=false unless cross-window amplitude is irrelevant. |
| newton_analyze_imageA | Ask Newton C a natural-language question about exactly one image. Provide exactly one of: image_base64 (with mime_type image/png or image/jpeg), sent inline as a data.base64_img event; or file_id, an existing Files API file_id (must end in .png/.jpg/.jpeg). This tool never uploads or stores anything -- it makes one read-only call to /query. |
| newton_propose_actionB | Propose exactly one validated Physical Action Contract from a physical-world observation, by calling Newton C with a strict JSON system prompt. Returns either a schema-valid contract or a failure with the raw model text and validation errors -- never a guessed, defaulted or partially filled contract. This tool only proposes an action; it never executes or authorises one. |
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 4 tools
Tools have mostly distinct purposes: analyze_image for image Q&A, propose_action for action contracts, embed_timeseries for embeddings, and query for general text/JSON Q&A. Potential overlap exists between query and analyze_image since both ask natural-language questions, and query's structured JSON capability could be confused with propose_action, though descriptions clarify boundaries.
All tools share a consistent 'newton_' prefix, and three of four follow a verb_noun pattern (analyze_image, propose_action, embed_timeseries). The bare verb 'newton_query' is a minor deviation but remains readable and predictable.
Four tools is a well-scoped set for a model gateway, each covering a distinct capability (image, action, embedding, query). The count is within the ideal 3–15 range, and no tool feels redundant or missing from the core set.
The surface covers key interactions with Newton C: querying, image analysis, action proposal, and timeseries embedding. A file upload tool is absent, but the tools accept base64 inline or pre-existing file_ids, so agents can work around it; no execution tool is expected by design.