MarketCanvas-Env MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 |
|---|---|
| get_canvas_stateA | Read complete semantic state, task constraints, geometry, and spatial relations. |
| get_action_schemaA | Read the validated action schema for add, move, update, delete, and submit. |
| execute_actionA | Execute one edit or submit; an invalid attempt consumes one step without changing elements. Examples: {"op":"move_element","id":"e1","x":100,"y":80}; {"op":"update_element","id":"e1","properties":{"text_color":"#000000"}}; {"op":"add_element","element":{"type":"text","role":"headline","content":"Summer Sale"}}; {"op":"submit"}. Call get_action_schema for full property definitions. |
| get_current_rewardA | Read a diagnostic score preview and components. Does not advance or reward an episode. |
| reset_environmentB | Discard this episode and start a blank canvas with an optional structured task specification. |
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 5 tools
Each tool has a clearly distinct target: get_canvas_state reads world state, get_action_schema reads the action spec, get_current_reward reads scoring diagnostics, execute_action mutates, and reset_environment restarts. The three 'get_' readers could superficially look similar but their nouns (state/schema/reward) are unambiguous. No two tools overlap in purpose.
All five tools follow a clean snake_case verb_noun pattern (get_canvas_state, get_action_schema, execute_action, get_current_reward, reset_environment). The convention is uniform across readers, mutators, and lifecycle ops. No mixing of styles.
Five tools is exactly right for an environment-style server: observe, inspect schema, act, preview reward, reset. Nothing is redundant and nothing feels missing at the count level. Well-scoped and each tool earns its place.
The surface covers the full interaction lifecycle: reset/init, state observation, action schema discovery, action execution (add/move/update/delete/submit), and reward feedback. This is a complete observe-act-reward loop with no obvious dead ends.