{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_3ssyn66298k5","handle":"iflow-mcp-hritik003-linkedin-mcp","url":"https://wellknown.network/agents/iflow-mcp-hritik003-linkedin-mcp","links":{"self":"https://wellknown.network/agents/iflow-mcp-hritik003-linkedin-mcp/record.json","html":"https://wellknown.network/agents/iflow-mcp-hritik003-linkedin-mcp","markdown":"https://wellknown.network/agents/iflow-mcp-hritik003-linkedin-mcp/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-hritik003-linkedin-mcp","status":"https://wellknown.network/api/v1/agents/iflow-mcp-hritik003-linkedin-mcp/status","claim":"https://wellknown.network/agents/iflow-mcp-hritik003-linkedin-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-hritik003-linkedin-mcp/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-hritik003-linkedin-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-hritik003-linkedin-mcp/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-hritik003-linkedin-mcp/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-hritik003-linkedin-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_hritik003_linkedin-mcp","summary":"Add your description here","description":"# MCP Server for LinkedIn\n\n[![smithery badge](https://smithery.ai/badge/@Hritik003/linkedin-mcp)](https://smithery.ai/server/@Hritik003/linkedin-mcp)\n\nA Model Context Protocol (MCP) server for linkedin to apply Jobs and search through feed seamlessly. \n\nThis uses Unoffical [Linkedin API Docs](https://linkedin-api.readthedocs.io/en/latest/api.html) for hitting at the clients Credentials.\n\n## Features\n\n1. **Profile Retrieval**\n\n    Fetch user profiles using `get_profile()` function\n    Extract key information such as `name`, `headline`, and `current position`\n\n2. **Job Search**\n\n  - Advanced job search functionality with multiple parameters:\n      - Keywords\n      - Location\n      - Experience level\n      - Job type (Full-time, Contract, Part-time)\n      - Remote work options\n      - Date posted\n      - Required skills\n  - Customizable search limit\n\n3. **Feed Posts**\n\n  - Retrieve LinkedIn feed posts using `get_feed_posts()`\n  - Configurable limit and offset for pagination\n  \n4. **Resume Analysis**\n\n  - Parse and extract information from `resumes (PDF format)`\n  - Extracted data includes:\n      - Name\n      - Email\n      - Phone number\n      - Skills\n      - Work experience\n      - Education\n      - Languages\n\n---\n\n# Configuration\n\nAfter cloning the repo, adjust the `<LOCAL_PATH>` accordingly\n\n```python\n{\n    \"linkedin\":{\n        \"command\":\"uv\",\n        \"args\": [\n            \"--directory\",\n            \"<LOCAL_PATH>\",\n            \"run\",\n            \"linkedin.py\"\n        ]\n    }   \n}     \n\n```\n\n---\n\n# Usage\n\nI have been testing using [MCP-client](https://github.com/chrishayuk/mcp-cli) and found as the best one for testing your `MCP-Servers`.","publisher":null,"homepage":"https://github.com/Hritik003/linkedin-mcp","repository":"https://github.com/Hritik003/linkedin-mcp","version":"0.1.0","license":null,"protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_hritik003_linkedin-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"content.social","name":"Social Media","confidence":1,"provenance":"derived"}],"categories":["content"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp_hritik003_linkedin-mcp","registry":"pypi","observedAt":"2026-11-09T08:25:03.432Z","publishedAt":"2025-12-31T07:15:57.021917Z","latestVersion":"0.1.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_hritik003_linkedin-mcp","url":"https://pypi.org/project/iflow-mcp_hritik003_linkedin-mcp/","firstSeenAt":"2026-09-09T19:23:41.142Z","fetchedAt":"2026-11-09T08:24:06.467Z","normalizedAt":"2026-11-09T08:24:06.467Z"}]},"firstSeenAt":"2026-09-09T19:23:41.142Z","updatedAt":"2026-11-09T08:25:03.432Z"}