Schema | resume-tailor-mcp

resume-tailor-mcp

Describes the environment variables required to run the server.

Name	Required	Description	Default
`TAILOR_MODE`	No	Select the LLM backend (default: 'api'). Set to 'sampling' for key-less operation.	api
`ANTHROPIC_API_KEY`	No	Your Anthropic API key. Required for the 'api' backend.

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.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{ "listChanged": true }

Functions exposed to the LLM to take actions

Name	Description
pingA	Health check. Returns 'pong', echoing an optional message.
tailor_resumeA	Tailor a resume to a specific job description without fabricating experience. Returns a fit score, matched/missing keywords, truthful rewrites of existing bullets, honest gaps, and a short cover note.
score_fitA	Score how well a resume fits a job posting on a 1-5 scale (with a recommendation), and separately judge whether the posting looks like a real, active opening. Use it to triage which roles deserve a full tailor.
extract_keywordsA	Extract the keywords an applicant-tracking system would key on from a job posting, grouped into must-have and nice-to-have.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mr-martinsosa/resume-tailor-mcp'

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