Searches multiple job boards, scores listings for fit, and provides a local ranked board for triage in Claude Desktop.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Job Search MCP.
find_jobsSearch the boards for your roles/location (with optional filters: seniority, type, recency, remote, salary, applicants, source).
evaluate_jobsClaude scores the found jobs 0β100 for fit (runs automatically after a search).
show_boardDisplay the ranked board (or your `saved` tracker).
set_statusApply / Skip / save a single job (also the card buttons).
bulk_statusTriage many at once by score or source, e.g. *dismiss everything under 60*.
whats_promisingList the current board as text (all scored jobs + anything still unscored).
Servation/job-search-mcp MCP server combines job discovery, fit evaluation, and application triage in a local workflow. Searches cover LinkedIn and eight additional sources: Greenhouse, Lever, Ashby, Workday, SmartRecruiters, Hacker News, RemoteOK, and Remotive. Queries can target roles and locations, with optional filters for seniority, employment type, posting age, remote status, salary, applicant count, and source.
After a search, Claude reads the available job descriptions and assigns each listing a fit score from 0 to 100, along with a short reason. The resulting shortlist can be displayed as an inline board. Listings can be applied to, skipped, or saved individually, and multiple entries can be triaged by score or source. The project is tuned for US software-engineering roles, so searches outside that scope may return limited results.
The MCP server runs locally over stdio and communicates with Claude Desktop. Its accompanying MCP App UI is bundled as a single HTML resource that renders the ranked board inside a compatible host. Claude selects the exposed tools during normal conversation; users can request actions such as finding jobs, showing the board, or reviewing saved applications without manually invoking tool names.
A profile can be saved from a resume. The profile supplies skills, roles, experience, and location information used by later searches and scoring. The host model performs the normal evaluation directly, so the project does not require a separate LLM API key. A deterministic scoring fallback exists in the source for weaker local models, but it is not enabled by default.
The board acts as a persistent shortlist. New searches avoid jobs already on the board, in the tracker, dismissed, or shown within the previous six months. Applied jobs move to the tracker, while skipped jobs are hidden. The data is stored in one JSON file on the local machine and is not sent to a service other than the job boards being searched.
Servation/job-search-mcp MCP server can be added to Claude Desktop with the published npm package:
After changing the configuration, fully quit and reopen Claude Desktop. The documented configuration locations are %APPDATA%\\Claude\\claude_desktop_config.json on Windows and ~/Library/Application Support/Claude/claude_desktop_config.json on macOS. Developers running from source can install dependencies, build the project, and point the configuration to the generated dist/main.js file.
By default, job data is stored at ~/.job-search-mcp/jobs.json for an installed package or ./data/jobs.json when running from source. JOB_SEARCH_MCP_DATA can override that location.
The server exposes tools for:
Servation/job-search-mcp MCP server is built and tested for Claude Desktop. It should also work with MCP clients that support local stdio servers and MCP App UIs, including Cursor, but other listed examples are untested. Remote-only clients such as Claude on the web or mobile cannot launch the local server.
LinkedIn uses public guest endpoints by default. An optional logged-in mode accepts LINKEDIN_LI_AT and LINKEDIN_JSESSIONID, but the README warns that automated logged-in access may violate LinkedInβs terms, can lead to account restrictions, and depends on cookies and internal endpoints that may expire or change. If that mode fails, the server falls back to guest access.
Job-source availability can change, and company slugs may become outdated. The repository includes a canary command for checking whether sources still return postings. No account or API key is required for the default setup.
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