--- title: "askimo vs linkedin-mcp-server" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/askimo-ai-askimo-vs-stickerdaniel-linkedin-mcp-server" tools: ["askimo-ai-askimo", "stickerdaniel-linkedin-mcp-server"] --- # askimo vs linkedin-mcp-server *GraphCanon updated Aug 26, 2026* ## Verdict Pick askimo when askimo is primarily Kotlin; linkedin-mcp-server is Python; pick linkedin-mcp-server when linkedin-mcp-server is primarily Python; askimo is Kotlin. [askimo](https://askimo.chat) reports 318 GitHub stars, 66 forks, and 19 open issues, last pushed Aug 13, 2026. [linkedin-mcp-server](https://github.com/stickerdaniel/linkedin-mcp-server) has 3.2k stars, 559 forks, and 150 open issues, last pushed Aug 25, 2026. Figures are from public GitHub metadata via [askimo's repository](https://github.com/askimo-ai/askimo) and [linkedin-mcp-server's repository](https://github.com/stickerdaniel/linkedin-mcp-server). | | [askimo](/tools/askimo-ai-askimo.md) | [linkedin-mcp-server](/tools/stickerdaniel-linkedin-mcp-server.md) | | --- | --- | --- | | Tagline | AI Client for chat, RAG, and agents with multi-provider model support. | Open-source MCP server for LinkedIn enabling access to profiles, companies, jobs, and messages. | | Stars | 318 | 3,222 | | Forks | 66 | 559 | | Open issues | 19 | 150 | | Language | Kotlin | 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. | | Persona | - | - | | Runtime | - | - | | License | AGPL-3.0 | Apache-2.0 | | Categories | AI Agents, Data & Retrieval | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [askimo](/tools/askimo-ai-askimo.md) | [linkedin-mcp-server](/tools/stickerdaniel-linkedin-mcp-server.md) | | --- | --- | --- | | Open issues (now) | 19 | 150 | | Stars delta | Unknown | +315 (30d) | | Open issues delta | Unknown | +65 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/askimo-ai-askimo/trust.md) | [trust report](/tools/stickerdaniel-linkedin-mcp-server/trust.md) | ## Decision facts: askimo - **Pricing:** unknown - The pricing information on the Askimo repository is not specified. ## 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. ## Choose when ### Choose askimo if… - askimo is primarily Kotlin; linkedin-mcp-server is Python. - License: askimo is AGPL-3.0, linkedin-mcp-server is Apache-2.0. - Pricing: The pricing information on the Askimo repository is not specified.. - Tags unique to askimo: agentic-workflow, ai-assistant, artificial-intelligence, chat-client. - Use for Kotlin developers who need to integrate chat and AI agents with multi-provider support including Claude, Codex, Gemini, and OpenAI. ### Choose linkedin-mcp-server if… - linkedin-mcp-server is primarily Python; askimo is Kotlin. - License: linkedin-mcp-server is Apache-2.0, askimo is AGPL-3.0. - Tags unique to linkedin-mcp-server: claude-ai, linkedin-api, mcp-server. - 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 NOT to use askimo - Avoid if you require a solution that supports languages other than Kotlin, as Askimo is exclusively built for Kotlin environments. - Not suitable if your project has strict licensing requirements and requires proprietary code, due to its AGPL-3.0 license which might impose restrictions. ## 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 ## Common questions ### What is the difference between askimo and linkedin-mcp-server? askimo: AI Client for chat, RAG, and agents with multi-provider model support.. linkedin-mcp-server: Open-source MCP server for LinkedIn enabling access to profiles, companies, jobs, and messages.. See the comparison table for live GitHub stats and shared categories. ### When should I choose askimo over linkedin-mcp-server? Choose askimo over linkedin-mcp-server when askimo is primarily Kotlin; linkedin-mcp-server is Python; License: askimo is AGPL-3.0, linkedin-mcp-server is Apache-2.0; Pricing: The pricing information on the Askimo repository is not specified.; Tags unique to askimo: agentic-workflow, ai-assistant, artificial-intelligence, chat-client; Use for Kotlin developers who need to integrate chat and AI agents with multi-provider support including Claude, Codex, Gemini, and OpenAI. ### When should I choose linkedin-mcp-server over askimo? Choose linkedin-mcp-server over askimo when linkedin-mcp-server is primarily Python; askimo is Kotlin; License: linkedin-mcp-server is Apache-2.0, askimo is AGPL-3.0; Tags unique to linkedin-mcp-server: claude-ai, linkedin-api, mcp-server; 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 avoid askimo? Avoid if you require a solution that supports languages other than Kotlin, as Askimo is exclusively built for Kotlin environments. Not suitable if your project has strict licensing requirements and requires proprietary code, due to its AGPL-3.0 license which might impose restrictions. ### 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 ### Is askimo or linkedin-mcp-server more popular on GitHub? linkedin-mcp-server has more GitHub stars (3,222 vs 318). Stars measure visibility, not whether either tool fits your constraints. ### Are askimo and linkedin-mcp-server open source? Yes - both are open-source projects on GitHub (askimo: AGPL-3.0, linkedin-mcp-server: Apache-2.0). ### Where can I find alternatives to askimo or linkedin-mcp-server? GraphCanon lists graph-backed alternatives at [askimo alternatives](/tools/askimo-ai-askimo/alternatives) and [linkedin-mcp-server alternatives](/tools/stickerdaniel-linkedin-mcp-server/alternatives) ([askimo markdown twin](/tools/askimo-ai-askimo/alternatives.md), [linkedin-mcp-server markdown twin](/tools/stickerdaniel-linkedin-mcp-server/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/askimo-ai-askimo-vs-stickerdaniel-linkedin-mcp-server.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, askimo or linkedin-mcp-server? askimo: Very active. linkedin-mcp-server: 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 askimo and linkedin-mcp-server? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [askimo trust report](/tools/askimo-ai-askimo/trust); [linkedin-mcp-server trust report](/tools/stickerdaniel-linkedin-mcp-server/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=askimo-ai-askimo`](/api/graphcanon/graph?tool=askimo-ai-askimo) - 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/_