Resume Matching Agent
Open-source Python project that uses LangGraph, semantic search, and MCP to discover and process resumes through a filesystem MCP server, ranking candidates ag…
What it does
The specific capability behind this listing, and where to get it.
Resume Matching Agent
Open-source Python project that uses LangGraph, semantic search, and MCP to discover and process resumes through a filesystem MCP server, ranking candidates ag…
Agentery has not yet captured structured capability detail for this provider.
Official Resume Matching Agent links
Source repository available · no commercial pricing observed.
No price does not imply the product is free. Any code-host platform pricing is excluded.
Is Resume Matching Agent good value?
Price is straightforward; the useful comparison is capability, compatibility and operational cost.
Source repository available · no commercial pricing observed.
A public repository, but no identified licence or self-host evidence yet — so open-source / free-to-self-host is not asserted.
Check capability before deciding
Compare capability, compatibility and operational cost against comparable providers — Agentery keeps the price status explicit and never invents a verdict.
Resume Matching Agent's local market
Nearest products by what they do — a different cohort from the buyer-tier benchmark above.
See the MCP response behind this page · get_provider_profile()
See the MCP response behind this pageget_provider_profile (get_agent_profile remains a callable alias)
{
"agent_id": "resume_matching_agent",
"name": "Resume Matching Agent",
"url": "https://github.com/priyaulakshmi-commits/MCP-integration",
"logo": "https://github.com/priyaulakshmi-commits.png?size=200",
"niche": null,
"category": null,
"short_summary": "Open-source Python project that uses LangGraph, semantic search, and MCP to discover and process resumes through a filesystem MCP server, ranking candidates ag…",
"task_performed": "unclear",
"inputs_accepted": [],
"outputs_produced": [],
"integrations_available": [],
"protocols_or_interfaces": [],
"industry_fit": [],
"autonomy_level": "unclear",
"human_approval_needed": "unclear",
"pricing_model": "unclear",
"price": {
"observed": false,
"billing": "not_found",
"currency": null,
"lowest_monthly_usd": null,
"monthly_usd": null,
"headline": null,
"summary": null,
"confidence": "high",
"source_url": "https://github.com/pricing",
"checked_at": "2026-09-20T04:11:39.818Z",
"source_kind": "code_host",
"amount": null,
"display": null,
"plans": [],
"source": "render+llm"
},
"trust_or_rating_signal": [],
"evidence_quality": "unclear",
"entity_type": "github_project",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://github.com/priyaulakshmi-commits/MCP-integration"
],
"last_checked": null,
"how_to_connect": {
"website": "https://github.com/priyaulakshmi-commits/MCP-integration",
"docs": null,
"mcp": null,
"a2a": null,
"api": null,
"protocols": []
},
"liveness": {
"probed": true,
"alive": true,
"endpoint_kind": "site",
"latency_ms": 1048,
"uptime_7d": 1,
"checked_at": "2026-09-23T02:40:53.852Z",
"consecutive_failures": 0,
"status": "alive"
},
"price_extras": {
"free_tier": null,
"unit_cost": null
},
"reported_success": null,
"feedback": "If you actually use this provider, call report_outcome with the result. Testing Agentery's connection or retrieval is not provider use and is stored unweighted."
}