Skip to main content
Glama
l0kifs

project-explorer-mcp

by l0kifs

openapi_list_operations

List API operations from an OpenAPI spec. Filter by tag, method, or path to explore endpoints and summaries.

Instructions

List operations from an OpenAPI specification file.

Agent usage guidelines: - Use this tool when you need to explore the available API operations in an OpenAPI spec. - Use when you want to see endpoints, methods, and summaries without detailed schemas. - Do not use for getting detailed parameter or response information.

Path requirements: - The path must not contain URL-encoding (e.g., '%'). - The path must be absolute. - The path must exist on disk and be a valid OpenAPI JSON or YAML file.

Args: spec_path (str): Absolute path to the OpenAPI JSON or YAML file. output_format (str | None): Output format ('json' or 'markdown'). Defaults to server setting. filter_by_tag (str | None): Filter operations by tag. Only operations with this tag will be included. filter_by_method (str | None): Filter operations by HTTP method (e.g., 'GET', 'POST'). filter_by_path (str | None): Filter operations by path containing this substring (case-insensitive). limit (int): Maximum number of operations to return. Defaults to 50. offset (int): Number of operations to skip from the start. Defaults to 0.

Examples: - To get operations related to users: {"spec_path": "/path/to/spec.json", "filter_by_path": "user"} - To get all GET operations: {"spec_path": "/path/to/spec.json", "filter_by_method": "GET"} - To get operations with a specific tag: {"spec_path": "/path/to/spec.json", "filter_by_tag": "users"} - To paginate through results: {"spec_path": "/path/to/spec.json", "limit": 20, "offset": 40}

Returns: dict | str: For format_output="json": Dictionary containing operations list and metadata. - operations: list of operation dicts with method, path, operation_id, summary, tags - count: number of operations returned (after filtering and pagination) - total_count: total number of operations matching filters (before pagination) - error: error message if any, None otherwise For format_output="markdown": formatted markdown string

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
spec_pathYes
filter_by_tagNo
output_formatNo
filter_by_pathNo
filter_by_methodNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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 thoroughly describes behavior: filtering, pagination, output formats, return structure (operations, count, total_count, error), and path requirements (absolute, no URL-encoding, must exist and be valid). This goes well beyond a simple summary.

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?

Though the description is long, it is well-structured with sections (Agent usage guidelines, Path requirements, Args, Examples, Returns). Each section provides essential information without redundancy. The main purpose is front-loaded, and all content earns its place.

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

Completeness5/5

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

The tool has 7 parameters, no annotations, and no output schema. The description covers all aspects comprehensively: purpose, usage, parameter semantics, examples, return format, and edge cases. It is fully self-contained for an agent to select and invoke the tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, but the description compensates with an Args section that explains every parameter in plain language, including defaults and example values. The examples further illustrate usage with realistic JSON inputs, making the parameter semantics completely clear.

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 opens with 'List operations from an OpenAPI specification file', which clearly specifies the verb (list) and resource (operations in an OpenAPI spec). It distinguishes itself from siblings by explicitly noting it's for exploring endpoints, methods, and summaries without detailed schemas, which contrasts with sibling 'openapi_get_operation_details'.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance with bullet points: 'Use this tool when...' and 'Do not use for...'. It clearly states the scenarios for use (exploring available operations) and the exclusion (detailed parameter/response information), which implicitly points to the sibling getting details tool.

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/l0kifs/project-explorer-mcp'

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