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MCPGuard: Finding Conformance Gaps in MCP SDKs via Dual-Track Analysis and Dynamic Adjudication

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Briefings

MCPGuard is an automated LLM-based framework designed to detect specification-to-SDK conformance gaps in Model Context Protocol (MCP) SDKs. It operates via two tracks: a structural track aligning JSON Schema constraints with normalized SDK models, and a behavioral track extracting normative prose rules and auditing them with LLMs. An evidence-aware dynamic adjudicator then inspects complete source context to build Proof of Concepts (PoCs) validating candidates. The framework was tested on official Python 1.26.0 and TypeScript 1.29.0 SDKs, confirming 13 and 19 findings respectively, none of which were exposed by existing black-box baselines. These gaps can systematically propagate downstream when not addressed.

Key points

• MCPGuard uses a dual-track approach combining structural alignment of JSON Schema constraints with normalized SDK models and behavioral auditing of normative prose rules.
• The framework identified 13 conformance gaps in the official Python 1.26.0 SDK and 19 gaps in the TypeScript 1.29.0 SDK, findings not detected by existing black-box conformance tools.

Context

The Model Context Protocol (MCP) enables large language model agents to connect to external tools and services through official SDKs. Existing conformance tools primarily test running endpoints, failing to reveal whether SDK models enforce specification requirements. MCPGuard fills this gap by automating the detection of specification-to-SDK conformance gaps.

Limitations

Evidence is limited to official Python 1.26.0 and TypeScript 1.29.0 SDKs; open MCP server testing showed gaps propagate downstream but specific propagation mechanisms were not fully characterized.

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