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update_project_collaborator

Modify collaborator access levels in QuantConnect projects to adjust live control permissions for specific users.

Instructions

Update collaborator permissions in a project.

Args: project_id: ID of the project containing the collaborator collaborator_user_id: User ID of the collaborator to update live_control: Whether to grant live control permission (optional)

Returns: Dictionary containing update result

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYes
collaborator_user_idYes
live_controlNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function for the 'update_project_collaborator' tool. Decorated with @mcp.tool() which also serves as its registration. It authenticates, prepares a POST request to QuantConnect's projects/collaboration/update endpoint, and handles the response, returning structured success/error results.
    @mcp.tool()
    async def update_project_collaborator(
        project_id: int, collaborator_user_id: str, live_control: Optional[bool] = None
    ) -> Dict[str, Any]:
        """
        Update collaborator permissions in a project.
    
        Args:
            project_id: ID of the project containing the collaborator
            collaborator_user_id: User ID of the collaborator to update
            live_control: Whether to grant live control permission (optional)
    
        Returns:
            Dictionary containing update result
        """
        auth = get_auth_instance()
        if auth is None:
            return {
                "status": "error",
                "error": "QuantConnect authentication not configured. Use configure_auth() first.",
            }
    
        try:
            # Prepare request data
            request_data = {
                "projectId": project_id,
                "collaboratorUserId": collaborator_user_id,
            }
            
            if live_control is not None:
                request_data["liveControl"] = live_control
    
            # Make API request
            response = await auth.make_authenticated_request(
                endpoint="projects/collaboration/update", method="POST", json=request_data
            )
    
            # Parse response
            if response.status_code == 200:
                data = response.json()
    
                if data.get("success", False):
                    return {
                        "status": "success",
                        "project_id": project_id,
                        "collaborator_user_id": collaborator_user_id,
                        "live_control": live_control,
                        "message": f"Successfully updated collaborator {collaborator_user_id} for project {project_id}",
                    }
                else:
                    # API returned success=false
                    errors = data.get("errors", ["Unknown error"])
                    return {
                        "status": "error",
                        "error": "Failed to update project collaborator",
                        "details": errors,
                        "project_id": project_id,
                        "collaborator_user_id": collaborator_user_id,
                    }
    
            elif response.status_code == 401:
                return {
                    "status": "error",
                    "error": "Authentication failed. Check your credentials and ensure they haven't expired.",
                }
    
            else:
                return {
                    "status": "error",
                    "error": f"API request failed with status {response.status_code}",
                    "response_text": (
                        response.text[:500]
                        if hasattr(response, "text")
                        else "No response text"
                    ),
                }
    
        except Exception as e:
            return {
                "status": "error",
                "error": f"Failed to update project collaborator: {str(e)}",
                "project_id": project_id,
                "collaborator_user_id": collaborator_user_id,
            }
  • The call to register_project_tools(mcp) which triggers the definition and registration of all project tools including 'update_project_collaborator' via its @mcp.tool() decorator.
    safe_print("🔧 Registering QuantConnect tools...")
    register_auth_tools(mcp)
    register_project_tools(mcp)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Update' implies mutation, the description doesn't specify required permissions, whether changes are reversible, what happens to existing permissions not mentioned, or error conditions. The return format is mentioned but not detailed.

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

Conciseness4/5

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

The description is efficiently structured with a clear purpose statement followed by Args and Returns sections. The main description is a single focused sentence, though the parameter documentation could be more integrated rather than in a separate section.

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?

For a mutation tool with 3 parameters and no annotations, the description provides basic purpose and parameter documentation. The presence of an output schema reduces the need to detail return values. However, it lacks important context about permissions, side effects, and relationships to sibling tools, making it incomplete for confident agent usage.

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?

With 0% schema description coverage, the description provides basic parameter documentation in the Args section, explaining what each parameter represents. However, it doesn't fully compensate for the schema gap - it doesn't explain parameter formats, constraints, or that 'live_control' is optional with a null default. The description adds some value but leaves important details unspecified.

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?

The description clearly states the action ('Update collaborator permissions') and resource ('in a project'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'create_project_collaborator' or 'delete_project_collaborator', but the verb 'Update' provides reasonable distinction from creation/deletion operations.

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?

No guidance is provided about when to use this tool versus alternatives. The description doesn't mention prerequisites (like needing existing collaborators), when not to use it, or how it relates to sibling tools like 'create_project_collaborator' or 'delete_project_collaborator' that also manage collaborators.

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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