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mltree-mcp

by yboulaamane
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Python
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open_map

Get the URL of the mltree map viewer, starting it in the background when needed, then share that link with the user to open the workflow map.

Instructions

Return the URL of the mltree map viewer (and start it if needed). Give the URL to the user.

Input Schema

NameRequiredDescriptionDefault
portNoViewer port (default $MLTREE_VIEW_PORT or 8765)
startNoStart the viewer in the background if it is not running
allow_runNoStart it with Run buttons enabled (only if the user asked to run steps from the map)

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.8.0
    • addedInput schema / properties / allow_run
      Added value: +{
+  "default": false,
+  "description": "Start it with Run buttons enabled (only if the user asked to run steps from the map)",
+  "title": "Allow Run",
+  "type": "boolean"
+}
  2. First observedv0.4.0

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden, and it does disclose the key side effect: the viewer may be started in the background. It says nothing about process lifetime, what happens if the port is occupied, or the security implication of enabling Run buttons, so meaningful gaps remain.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, zero filler, with the action and its conditional side effect front-loaded ahead of the delivery instruction.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the return value (a URL) needn't be explained, and the description covers the conditional start behavior. Minor gaps remain around failure modes and whether the started viewer persists, but nothing essential to invoking it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% – port defaults, the start flag, and the allow_run condition are all documented in the schema itself. The description adds no parameter meaning beyond that, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb and resource: return the URL of the mltree map viewer, and start it if needed. It is clearly distinguishable from siblings like export_map or get_pipeline, though it never names an alternative to contrast with.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Give the URL to the user' is a delivery instruction, not a selection rule. There is no statement of when to prefer this over export_map or get_pipeline, and no exclusions; usage context is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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