rest-api-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| REST_ENV_DIR | No | Additional directory to search for .env.mcp files containing REST_BEARER_TOKEN | |
| REST_BASE_URL | Yes | Base URL for all API requests (e.g. https://api.example.com/v1) | |
| REST_BEARER_TOKEN | No | Bearer token for authentication | |
| REST_RESPONSE_SIZE_LIMIT | No | Max response size in bytes before smart truncation (default: 50000) |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| rest_set_tokenA | Set the bearer token for this session (persists until server restart). Token resolution: 1) project .env.mcp REST_BEARER_TOKEN, 2) MCP config env var, 3) session token via rest_set_token. If none found on 401/403, ask the user for a token. |
| rest_requestA | Execute an HTTP request and return the full response (smart-truncated if large). Base URL: https://api.example.com/v1 | Token resolution: 1) project .env.mcp REST_BEARER_TOKEN, 2) MCP config env var, 3) session token via rest_set_token. If none found on 401/403, ask the user for a token.. Responses over 50000 bytes are smart-truncated. Use rest_describe for structure only, or rest_types for TypeScript interfaces. AUTONOMOUS CONTEXT RESOLUTION — When the endpoint comes from code analysis (feature-port, migration, Vuex store dispatch, API service file): DO NOT call blindly with missing parameters. First investigate the source code context:
|
| rest_describeA | Execute an HTTP request and return the response structure (keys, types, array lengths) AND generated TypeScript interfaces — without the full body. Ideal for large responses. PRIMARY PURPOSE: The main goal of API response analysis is to derive TypeScript type definitions. Always present the generated TypeScript interfaces without being asked — this is the expected output for feature ports and migrations. Base URL: https://api.example.com/v1. AUTONOMOUS CONTEXT RESOLUTION — When the endpoint comes from code analysis (feature-port, migration, Vuex store dispatch, API service file): DO NOT call blindly with missing parameters. First investigate the source code context:
|
| rest_typesA | Execute an HTTP request and generate TypeScript interfaces from the response structure. This is the PRIMARY tool for feature-port and migration workflows — returns clean, ready-to-use TypeScript interfaces. PRIMARY PURPOSE: The main goal of API response analysis is to derive TypeScript type definitions. Always present the generated TypeScript interfaces without being asked — this is the expected output for feature ports and migrations. Base URL: https://api.example.com/v1. AUTONOMOUS CONTEXT RESOLUTION — When the endpoint comes from code analysis (feature-port, migration, Vuex store dispatch, API service file): DO NOT call blindly with missing parameters. First investigate the source code context:
|
| rest_extractA | Execute an HTTP request, then extract specific fields using dot-notation paths. Returns only the extracted data. Example: fields ["data.items[].name", "meta.total"]. Base URL: https://api.example.com/v1. AUTONOMOUS CONTEXT RESOLUTION — When the endpoint comes from code analysis (feature-port, migration, Vuex store dispatch, API service file): DO NOT call blindly with missing parameters. First investigate the source code context:
|
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
rest_describe and rest_types have nearly identical purposes (both generate TypeScript interfaces from response structure), causing serious overlap. rest_extract also executes a full request but only returns specific fields, further blurring the lines. Only rest_request and rest_set_token are clearly distinct.
Names follow a consistent verb_noun pattern (rest_set_token, rest_request, rest_describe, rest_types, rest_extract). However, 'rest_types' breaks the verb pattern (it's a verb+noun when 'generate_types' would be clearer), and the verbs are somewhat generic, but overall consistent.
With 5 tools, the count is appropriate for a REST API client MCP server. It covers token management, basic requests, structure discovery, type generation, and field extraction — a reasonable scope. Not over or under.
The tool set covers the main API interaction needs but has notable gaps: there is no tool for batch requests, no explicit schema validation or endpoint discovery without making a call, and no way to list available endpoints. An agent might need to make multiple calls to understand API structure.