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ispyridis

Calibre RAG MCP Server

by ispyridis

get_project_info

Retrieve detailed information about a specific RAG project within the Calibre ebook library, including its configuration, contents, and organization for semantic search and contextual conversations.

Instructions

Get detailed information about a specific RAG project

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_nameYesName of the project

Implementation Reference

  • The main handler function for the 'get_project_info' tool. It validates the project_name argument, retrieves the project configuration from the in-memory projects Map, and sends a formatted JSON-RPC success response with project details.
    case 'get_project_info':
        const infoProjName = args.project_name;
        
        if (!infoProjName) {
            this.sendError(id, -32602, 'Missing required parameter: project_name');
            return;
        }
        
        const project = this.projects.get(infoProjName);
        if (!project) {
            this.sendError(id, -32603, `Project '${infoProjName}' not found`);
            return;
        }
        
        this.sendSuccess(id, {
            content: [{
                type: 'text',
                text: `**Project: ${project.name}**\n\n` +
                    `Description: ${project.description}\n` +
                    `Created: ${project.created_at}\n` +
                    `Books: ${project.books.length}\n` +
                    `Chunks: ${project.chunk_count}\n` +
                    `Vector Dimension: ${project.vector_dimension}\n` +
                    `${project.last_updated ? `Last Updated: ${project.last_updated}` : ''}`
            }],
            project: project
        });
        break;
  • server.js:1072-1085 (registration)
    Tool registration in the tools/list response, including the tool name, description, and input schema definition (JSON Schema for parameters).
    {
        name: 'get_project_info',
        description: 'Get detailed information about a specific RAG project',
        inputSchema: {
            type: 'object',
            properties: {
                project_name: {
                    type: 'string',
                    description: 'Name of the project'
                }
            },
            required: ['project_name']
        }
    }
  • JSON Schema defining the input parameters for the 'get_project_info' tool: requires a 'project_name' string.
    inputSchema: {
        type: 'object',
        properties: {
            project_name: {
                type: 'string',
                description: 'Name of the project'
            }
        },
        required: ['project_name']
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get'), but doesn't mention potential side effects, authentication requirements, rate limits, error conditions, or what 'detailed information' includes. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple lookup tool and front-loads the essential information.

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 simple read operation with one parameter and no output schema, the description is minimally adequate. However, without annotations or output schema, it doesn't explain what 'detailed information' includes or potential behavioral aspects. Given the low complexity, it meets basic needs but could be more complete.

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?

The input schema has 100% description coverage, with the single parameter 'project_name' clearly documented. The description doesn't add any parameter-specific information beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.

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 verb ('Get') and resource ('detailed information about a specific RAG project'), making the purpose immediately understandable. However, it doesn't distinguish this tool from potential siblings like 'list_projects' or 'search_project_context', which might also retrieve project information in different ways.

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 like 'list_projects' or 'search_project_context'. It mentions 'specific RAG project', which implies it's for individual projects, but doesn't explicitly state this or provide exclusion criteria or prerequisites.

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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