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Linkedin Ops

github.com/yasir-ali9/linkedin-ops official repository

An MCP server for AI assistants to search LinkedIn job posts, save them to a local SQLite database, and manage them through natural-language commands or a Reac…

MCP serverSource repositoryRepository checked daily
Agentery price verdictNo pricing observedsource repository
SourcePublic repositorylicence not verified
Connection modelMCP serverMCP clients
Last checkedpricing & liveness

What it does

The specific capability behind this listing, and where to get it.

Linkedin Ops

An MCP server for AI assistants to search LinkedIn job posts, save them to a local SQLite database, and manage them through natural-language commands or a Reac…

Agentery has not yet captured structured capability detail for this provider.

Official Linkedin Ops links

Price status · observed daily

Source repository available · no commercial pricing observed.

No price does not imply the product is free. Any code-host platform pricing is excluded.

MCP

Is Linkedin Ops good value?

Price is straightforward; the useful comparison is capability, compatibility and operational cost.

Source repository

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.

Observed commercial pricenone
Hosting model
Price benchmarknot applicable
What to compare instead

Check capability before deciding

Compare language support, semantic depth, installation model against comparable providers — Agentery keeps the price status explicit and never invents a verdict.

See the MCP response behind this page · get_agent_profile()
See the MCP response behind this pageget_agent_profile
{
  "agent_id": "linkedin_ops",
  "name": "Linkedin Ops",
  "url": "https://github.com/yasir-ali9/linkedin-ops",
  "logo": "https://github.com/yasir-ali9.png?size=200",
  "niche": null,
  "category": null,
  "short_summary": "An MCP server for AI assistants to search LinkedIn job posts, save them to a local SQLite database, and manage them through natural-language commands or a Reac…",
  "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": null,
  "trust_or_rating_signal": [],
  "evidence_quality": "unclear",
  "entity_type": "mcp_server",
  "regulated_data_suitability": "unclear",
  "evidence_urls": [
    "https://github.com/yasir-ali9/linkedin-ops"
  ],
  "last_checked": null,
  "how_to_connect": {
    "website": "https://github.com/yasir-ali9/linkedin-ops",
    "docs": null,
    "mcp": null,
    "a2a": null,
    "api": null,
    "protocols": []
  },
  "liveness": {
    "probed": false,
    "alive": null,
    "endpoint_kind": null,
    "latency_ms": null,
    "uptime_7d": null,
    "checked_at": null,
    "consecutive_failures": 0,
    "status": "unknown"
  },
  "price_extras": {
    "free_tier": null,
    "unit_cost": null
  },
  "reported_success": null,
  "feedback": "If you use this listing, call report_outcome afterwards — it sharpens rankings for everyone including you."
}