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jamesbrink

MCP Server for Coroot

list_projects

Retrieve all accessible projects from Coroot observability platform to view project IDs and names for authenticated users.

Instructions

List all accessible projects.

Returns a list of all projects that the authenticated user has access to. Each project includes its ID and name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Main MCP tool handler for 'list_projects'. Decorated with @mcp.tool() for registration and executes the tool logic by calling the impl helper.
    @mcp.tool()
    async def list_projects() -> dict[str, Any]:
        """List all accessible projects.
    
        Returns a list of all projects that the authenticated user has access to.
        Each project includes its ID and name.
        """
        return await list_projects_impl()  # type: ignore[no-any-return]
  • Helper implementation that fetches projects via CorootClient and formats the success response with count and projects list.
    @handle_errors
    async def list_projects_impl() -> dict[str, Any]:
        """List all accessible projects."""
        projects = await get_client().list_projects()
        return {
            "success": True,
            "count": len(projects),
            "projects": projects,
        }
  • CorootClient method that implements the actual API call to retrieve projects from the /api/user endpoint.
    async def list_projects(self) -> list[dict[str, Any]]:
        """List all accessible projects.
    
        Returns:
            List of project dictionaries.
        """
        # Get user info which includes projects list
        user_response = await self._request("GET", "/api/user")
        user_data: dict[str, Any] = user_response.json()
        projects: list[dict[str, Any]] = user_data.get("projects", [])
        return projects
  • Lazy client factory used by tool helpers to get the shared CorootClient instance.
    def get_client() -> CorootClient:
        """Get or create the client instance.
    
        Raises:
            ValueError: If no credentials are configured.
        """
        global _client
        if _client is None:
            try:
                _client = CorootClient()
            except ValueError as e:
                # Re-raise with more context
                raise ValueError(
                    "Coroot credentials not configured. "
                    "Please set COROOT_BASE_URL and either:\n"
                    "  - COROOT_USERNAME and COROOT_PASSWORD for automatic login\n"
                    "  - COROOT_SESSION_COOKIE for direct authentication\n"
                    "  - COROOT_API_KEY for data ingestion endpoints"
                ) from e
        return _client
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that it's a read operation (returns a list) and mentions authentication context ('authenticated user'), but lacks details on pagination, rate limits, or error behaviors. It adds basic context but misses deeper behavioral traits.

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 front-loaded with the core purpose in the first sentence, followed by details on return format. Both sentences earn their place by clarifying scope and output, with zero wasted words.

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?

Given the tool's low complexity (0 params, read-only list operation), an output schema exists, and no annotations are provided, the description is mostly complete. It covers purpose, scope, and return structure, but could improve by mentioning authentication requirements or list limitations more explicitly.

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

Parameters4/5

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

There are 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add param info, but that's acceptable here. Baseline is 4 for 0 parameters, as it doesn't need to compensate for any gaps.

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

Purpose5/5

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

The description clearly states the verb ('List') and resource ('all accessible projects'), specifying it returns projects the authenticated user can access. It distinguishes from siblings like 'get_project' (singular) and 'create_project' (write operation) by focusing on listing all accessible items.

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

Usage Guidelines4/5

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

The description implies usage when needing to see all accessible projects, with 'accessible' hinting at permission-based filtering. However, it doesn't explicitly state when not to use it or name alternatives like 'get_project' for single project details, leaving some ambiguity.

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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