resumessearchfile-systemsrecruitingdocument-processing
Searches local resume and application files, extracts structured data, and reloads indexes automatically when documents change.
Quick Install
Automated & IDE SetupCopy the AI prompt to install this server into Claude Code, Cursor, or another agent ā or use 1-click editor setup below.
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This server is confirmed live ā we successfully called its tools/list endpoint directly (see the verified badge above). We haven't yet sandbox-tested the stdio install command below specifically, which is a separate, ongoing check.
Manual Client & Custom JSON ConfigExpand JSON ā¾
Client Config & Setup
Choose your client or environment
Target File:
š” Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Overview
Use cases
Search resume versions for a specific skill
Compare work achievements across candidates
Retrieve education and project details for an application
Find documents containing a keyword or phrase
Track common skills across a local resume collection
Key features
Parses DOCX, PDF, Markdown, and text files
Indexes structured resume fields
Supports full-text and scoped entity search
Reloads changed files automatically
Deduplicates resume versions by identity
Provides collection and skill-frequency statistics
Capabilities & Tool Schemas (19)
Inspect callable tools, capabilities, and parameters exposed to AI agents by Resume MCP Server.
list_resume_summariesList resumes as lightweight identity records ā id, name, email, phone only. Use this to orient and pick a resume_id before fetching details with other tools. Much more token-efficient than list_resumes when you only need to identify who is present. Pass query to filter by first or last name (absorbs the old search_resumes_by_name tool). Response includes total_count and items for pagination.
get_resume_profileGet a resume's top-level fields (contact info, professional statement, education) without the nested work experience and badge skill lists. See also: get_resume_full for everything about this resume in one call. Returns {"error": ...} if resume_id is not found.
get_resume_fullGet a resume's complete nested structure in one call: profile fields plus all work experiences (with achievements), badge skills, side projects (with technologies), and education entries (with competencies). Prefer get_resume_profile plus the scoped list_* tools (list_work_experiences, list_skills, list_side_projects, list_education) when you only need part of this ā it's more token-efficient. Use get_resume_full when you need the whole picture at once. Returns {"error": ...} if resume_id is not found.
list_resumesList all documents. When doc_type is 'resume' (or omitted), structured resume data is returned if available; otherwise flat file metadata is returned. Response includes total_count and items for pagination. See also: list_resume_summaries for a lighter-weight, more token-efficient listing; get_resume_full for one resume's full nested structure by resume_id.
get_resumeReturn the full extracted text of a document, as {"text": "..."}. Note: takes a file path (see list_resumes), not a resume_id ā use get_resume_profile or list_resumes to fetch structured data by resume_id instead. Returns {"error": ...} if path is not found.
search_resumesSearch across all documents for a keyword or phrase. Response includes total_count, items, has_more, next_offset, and message for pagination.
How Resume MCP Server works
What mnoomnoo/resume-mcp-server MCP server does
The mnoomnoo/resume-mcp-server MCP server turns a local directory of resume and job-application documents into searchable MCP resources. It accepts .docx, .pdf, .md, and .txt files, extracts resume-oriented fields, and preserves both document text and structured records where available. Extracted data includes contact details, professional statements, work experience, achievements, badge skills, side projects, education, and related competencies.
The server is suited to collections containing multiple resume versions, cover letters, reference material, and other application documents. It can identify resumes by lightweight identity fields, retrieve complete or partial profiles, search document text, and filter structured entities by terms such as skill, company, role, technology, competency, or education. It also provides aggregate collection counts, average values, and skill-frequency rankings.
How it works
On startup, the server scans the configured document directory and builds an in-memory collection. A filesystem watcher re-indexes files when they change, so edits can be reflected without restarting the process. Files are classified as resumes, cover letters, application materials, or other documents using filename patterns; the README states that these classifications can be overridden through environment variables.
The mnoomnoo/resume-mcp-server MCP server uses resume IDs for structured lookups and file paths for full extracted-text retrieval. List operations return pagination metadata, including total counts and offsets where applicable. Query-style tools support consistent matching modes described by the project as and, or, and regular-expression matching. Responses use a common error object when a requested ID, path, or resume cannot be found.
Duplicate versions for the same person are matched by email or name and reduced to the richest available copy. Tools are read-only and are described as operating only on the local document collection; they do not modify source files.
Setup and configuration
Install the package with pip install resume-mcp-server, then run the resume-mcp-server executable. The quick-start configuration sets RESUME_DIR to the directory containing documents. If it is not supplied, the documented local default is ~/resumes.
The server can communicate over stdio or HTTP. FASTMCP_TRANSPORT selects the transport, while FASTMCP_HOST and FASTMCP_PORT configure HTTP binding and port. The README documents FASTMCP_PORT as defaulting to 8001. A .env file may provide configuration, with shell or MCP-client values taking precedence. Docker Compose can mount a host directory and expose the HTTP endpoint at /mcp.
Tools and capabilities
The mnoomnoo/resume-mcp-server MCP server includes tools for:
- Listing lightweight resume identities or complete document metadata.
- Retrieving profile-only, full nested, or raw extracted-text results.
- Searching all documents with keywords or phrases.
- Finding resumes by badge skill.
- Listing and retrieving work experiences and achievements.
- Listing and retrieving skills, side projects, and education entries.
- Filtering projects by technology and education by competency.
- Reporting collection statistics and skill frequency.
Scoped list tools can return smaller result shapes when only identifiers or matching fields are needed, which helps limit response size for agent workflows.
Limitations and notes
The server depends on the quality and structure of the source documents. The README points to a resume-formatting guide for better extraction results. Structured lookup and raw text retrieval use different identifiers, so callers should first inspect the listing or profile response before requesting details. The project requires Python 3.12 or newer for local development and execution.
Related MCP Servers
Adoption & maintenance
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GitHub stars
1
Stargazers on the source repository.
Last commit
1mo ago
Most recent push to the default branch.
Tools exposed
19
Callable tools this server registers over MCP.
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CategoryWorkplace & Productivity
PricingFree
10/13 checks healthy over the last 32d
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Scanned 20d ago via OSV.dev Ā· resume-mcp-server (PyPI)
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