--- title: "linkedin-mcp-server vs agents" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/stickerdaniel-linkedin-mcp-server-vs-wshobson-agents" tools: ["stickerdaniel-linkedin-mcp-server", "wshobson-agents"] --- # linkedin-mcp-server vs agents *GraphCanon updated Sep 20, 2026* ## Verdict Pick linkedin-mcp-server if linkedin-mcp-server is an open-source MCP server for LinkedIn that supports integration with various AI agents like Claude, offering access to profiles, companies, jobs, and messages; pick agents if the agents tool is a marketplace for plugins that enhances multiple AI agents, offering integration and management capabilities across several platforms, including Claude Code, Codex CLI, Cursor, OpenCode, GitHub. [linkedin-mcp-server](https://github.com/stickerdaniel/linkedin-mcp-server) reports 3.5k GitHub stars, 617 forks, and 187 open issues, last pushed Sep 19, 2026. [agents](https://sethhobson.com) has 40k stars, 4.2k forks, and 12 open issues, last pushed Sep 19, 2026. Figures are from public GitHub metadata via [linkedin-mcp-server's repository](https://github.com/stickerdaniel/linkedin-mcp-server) and [agents's repository](https://github.com/wshobson/agents). | | [linkedin-mcp-server](/tools/stickerdaniel-linkedin-mcp-server.md) | [agents](/tools/wshobson-agents.md) | | --- | --- | --- | | Tagline | Open-source MCP server for LinkedIn enabling access to profiles, companies, jobs, and messages. | Multi-harness agentic plugin marketplace for various AI agents | | Stars | 3,548 | 39,823 | | Forks | 617 | 4,246 | | Open issues | 187 | 12 | | Language | Python | Python | | Adopt for | linkedin-mcp-server is an open-source MCP server for LinkedIn that supports integration with various AI agents like Claude, offering access to profiles, companies, jobs, and messages. | The agents tool is a marketplace for plugins that enhances multiple AI agents, offering integration and management capabilities across several platforms, including Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Data & Retrieval | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [linkedin-mcp-server](/tools/stickerdaniel-linkedin-mcp-server.md) | [agents](/tools/wshobson-agents.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 187 | 12 | | Stars delta | +641 (30d) | +895 (30d) | | Open issues delta | +102 (30d) | +7 (30d) | | Full report | [trust report](/tools/stickerdaniel-linkedin-mcp-server/trust.md) | [trust report](/tools/wshobson-agents/trust.md) | ## Decision facts: linkedin-mcp-server - **Adopt for:** linkedin-mcp-server is an open-source MCP server for LinkedIn that supports integration with various AI agents like Claude, offering access to profiles, companies, jobs, and messages. ## Decision facts: agents - **Adopt for:** The agents tool is a marketplace for plugins that enhances multiple AI agents, offering integration and management capabilities across several platforms, including Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot ## Choose when ### Choose linkedin-mcp-server if… - License: linkedin-mcp-server is Apache-2.0, agents is MIT. - Tags unique to linkedin-mcp-server: claude-ai, linkedin-api, mcp-server. - Also covers Data & Retrieval. - linkedin-mcp-server ships Docker support for self-hosted deployment. - To integrate MCP-compatible AI agents like Claude specifically with LinkedIn data for tasks such as job analysis or network augmentation ### Choose agents if… - License: agents is MIT, linkedin-mcp-server is Apache-2.0. - Tags unique to agents: agent-skills, agentic-ai, automation, prompt-engineering. - Also covers Developer Tools. - You are working specifically within the ecosystems of Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, or Gemini CLI, as it provides tailored plugins for these environments ## When NOT to use linkedin-mcp-server - If your project requires a proprietary solution that does not need open-source contributions - For platforms or projects where support for the Model Context Protocol (MCP) is unnecessary or incompatible with existing workflows ## When NOT to use agents - You are working solely within a niche environment that isn't one of the supported platforms (like Claude Code, Codex CLI, etc.) because it may not offer compatible plugins or extensive support - Your project requirements do not include interoperability between multiple AI agents and you only need to leverage functionalities from a single AI agent with a robust in-built plugin ecosystem ## Common questions ### What is the difference between linkedin-mcp-server and agents? linkedin-mcp-server: Open-source MCP server for LinkedIn enabling access to profiles, companies, jobs, and messages.. agents: Multi-harness agentic plugin marketplace for various AI agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose linkedin-mcp-server over agents? Choose linkedin-mcp-server over agents when License: linkedin-mcp-server is Apache-2.0, agents is MIT; Tags unique to linkedin-mcp-server: claude-ai, linkedin-api, mcp-server; Also covers Data & Retrieval; linkedin-mcp-server ships Docker support for self-hosted deployment; To integrate MCP-compatible AI agents like Claude specifically with LinkedIn data for tasks such as job analysis or network augmentation. ### When should I choose agents over linkedin-mcp-server? Choose agents over linkedin-mcp-server when License: agents is MIT, linkedin-mcp-server is Apache-2.0; Tags unique to agents: agent-skills, agentic-ai, automation, prompt-engineering; Also covers Developer Tools; You are working specifically within the ecosystems of Claude Code, Codex CLI, Cursor, OpenCode, GitHub Copilot, or Gemini CLI, as it provides tailored plugins for these environments. ### When should I avoid linkedin-mcp-server? If your project requires a proprietary solution that does not need open-source contributions For platforms or projects where support for the Model Context Protocol (MCP) is unnecessary or incompatible with existing workflows ### When should I avoid agents? You are working solely within a niche environment that isn't one of the supported platforms (like Claude Code, Codex CLI, etc.) because it may not offer compatible plugins or extensive support Your project requirements do not include interoperability between multiple AI agents and you only need to leverage functionalities from a single AI agent with a robust in-built plugin ecosystem ### Is linkedin-mcp-server or agents more popular on GitHub? agents has more GitHub stars (39,823 vs 3,548). Stars measure visibility, not whether either tool fits your constraints. ### Are linkedin-mcp-server and agents open source? Yes - both are open-source projects on GitHub (linkedin-mcp-server: Apache-2.0, agents: MIT). ### Where can I find alternatives to linkedin-mcp-server or agents? GraphCanon lists graph-backed alternatives at [linkedin-mcp-server alternatives](/tools/stickerdaniel-linkedin-mcp-server/alternatives) and [agents alternatives](/tools/wshobson-agents/alternatives) ([linkedin-mcp-server markdown twin](/tools/stickerdaniel-linkedin-mcp-server/alternatives.md), [agents markdown twin](/tools/wshobson-agents/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/stickerdaniel-linkedin-mcp-server-vs-wshobson-agents.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, linkedin-mcp-server or agents? linkedin-mcp-server: Very active. agents: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for linkedin-mcp-server and agents? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [linkedin-mcp-server trust report](/tools/stickerdaniel-linkedin-mcp-server/trust); [agents trust report](/tools/wshobson-agents/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=stickerdaniel-linkedin-mcp-server`](/api/graphcanon/graph?tool=stickerdaniel-linkedin-mcp-server) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_