Skip to main content
Glama
i-dream-of-ai

QuantConnect MCP Server

update_project_collaborator

Idempotent

Modify collaborator permissions for a QuantConnect project to control code editing and live algorithm deployment rights.

Instructions

Update collaborator information in a project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
successNoIndicate if the API request was successful.
collaboratorsNoList of collaborators.
Behavior3/5

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

The annotations include 'idempotentHint: true,' which the description does not contradict, as 'update' can be idempotent. However, the description adds no behavioral context beyond this, such as permission requirements, side effects, or rate limits. With annotations covering idempotency, the description meets a baseline but fails to enrich understanding of the tool's behavior.

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?

The description is a single, clear sentence: 'Update collaborator information in a project.' It is front-loaded with the core action and resource, with no unnecessary words or redundancy. This makes it highly efficient and easy to parse, earning full marks for conciseness.

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

Completeness3/5

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

Given the tool's complexity as a mutation tool with 1 parameter (a nested object), 0% schema description coverage, and an output schema present, the description is minimally complete. It states the purpose but lacks details on usage, parameters, or behavioral traits. The output schema may cover return values, but the description does not provide enough context for effective tool selection and invocation.

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

Parameters2/5

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

The input schema has 0% description coverage, meaning parameter details like 'liveControl' and 'write' are only documented in the schema. The description adds no semantic information about parameters, such as what 'collaborator information' entails or how updates are applied. It does not compensate for the low schema coverage, leaving parameters poorly explained in the description.

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

Purpose3/5

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

The description states the tool's purpose as 'Update collaborator information in a project,' which is clear but vague. It specifies the verb ('update') and resource ('collaborator information in a project'), but does not differentiate from sibling tools like 'create_project_collaborator' or 'delete_project_collaborator' in terms of scope or specific actions. This makes it minimally adequate but lacking in specificity.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing an existing collaborator, or contrast with sibling tools like 'create_project_collaborator' for adding new collaborators or 'delete_project_collaborator' for removal. Without any usage context, it leaves the agent to infer appropriate scenarios.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/i-dream-of-ai/quantconnect-mcp-jwt'

If you have feedback or need assistance with the MCP directory API, please join our Discord server