ai-mcp
Host-side Model Context Protocol (MCP) client for TanStack AI: connect to external MCP servers, discover and run their tools inside any adapter's chat() loop, read resources and prompts, generate TypeScript types (typed tool names/pool keys) with the bundled CLI, and manage lifecycle with close()/await using.
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Low-risk findings worth noting
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Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required runtime workflow in this skill uses `chat()` with `mcp` / `tools` by calling `client.tools()` to ingest MCP server-discovered schemas and tool metadata into the model’s tool list.
W012: Unverifiable external dependency detected (runtime URL that controls agent).
What this means
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Why it was flagged
The skill examples show runtime connections to MCP servers (e.g., https://mcp.example.com/mcp, https://mcp.github.com/mcp, https://mcp.linear.app/mcp, https://mcp-app.example.com/mcp) whose tools, prompts, and resources are fetched at runtime and then injected into chat messages (thereby directly controlling model input); the stdio example also runs "npx my-mcp-server" which would execute fetched code at runtime.
- Repository
- TanStack/ai
- Commit
4e9c5d2
- Audited
- Security analysis
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