csharp-sdk: The official C# SDK for Model Context Protocol servers and clients. Maintained in collaboration with Microsoft

by modelcontextprotocol · MCP Server · ★ 4.6k

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Security audit verdict: SAFE · quality 62/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

csharpdotnetmcpmcp-clientmcp-servermodelcontextprotocol

Quick Facts

Stars4,616
Forks840
LanguageC#
CategoryMCP Server
Quality Score62/100
Open Issues213
Last Updated2026-11-07
Created2025-03-10
Platformsdotnet, mcp
Est. Tokens~18k

About csharp-sdk

MCP C# SDK The official C# SDK for the Model Context Protocol, enabling .NET applications, services, and libraries to implement and interact with MCP clients and servers. Please visit the API documentation for more details on available functionality.

Compatible Skills

These tools work well together with csharp-sdk for enhanced workflows:

  • mcp — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (54%)
  • fastmcp — semantic(0.30)+complementary+similar_pop+shared_platform (50%)
  • mcp-dotnet-samples — semantic(0.20)+complementary+same_lang+shared_platform (47%)
  • MCPSharp — semantic(0.32)+complementary+same_lang+shared_platform (46%)

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    [DEPRECATED] Legacy Klavis AI MCP integrations. See klavis.ai for RL environments and training data.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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