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mcp-code-execution

Scaffold the code execution pattern for MCP-based agents. Use when agents call many MCP tools, intermediate data exceeds context, you need loops, or PII must stay out of context.

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laurigates/claude-plugins
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29 juillet 2026 à 06:22
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SKILL.md
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name
mcp-code-execution
description
Scaffold the code execution pattern for MCP-based agents. Use when agents call many MCP tools, intermediate data exceeds context, you need loops, or PII must stay out of context.
user-invocable
false
allowed-tools
Bash, Read, Write, Edit, Grep, Glob, TodoWrite
created
2026-02-08T00:00:00.000Z
modified
2026-07-28T00:00:00.000Z
reviewed
2026-06-14T00:00:00.000Z
# MCP Code Execution Pattern Expert knowledge for designing agent systems that generate and execute code to interact with MCP servers, instead of calling tools directly. For the typed-wrapper code, the six key-pattern examples, and the project scaffolding steps, see [REFERENCE.md](REFERENCE.md). ## When to Use This Skill | Use code execution when... | Use direct tool calls / `mcp-management` when... | |----------------------------|--------------------------------------------------| | Designing agents that fan out across 10+ MCP servers or 50+ tools | Installing or configuring one or two servers in `.mcp.json` | | Intermediate results are large (>10K tokens) and would blow context | Results are small and all needed by the model | | Workflows need loops, retries, or conditionals across tool calls | Linear sequences of 2–3 tool calls | | PII must not reach the model context | Tool responses contain no sensitive data | | Tasks benefit from state persistence across runs | Stateless, one-shot operations | | You want agents to accumulate reusable skills | Fixed, predefined workflows | ## Core Architecture ### How It Works Instead of loading all MCP tool definitions into context upfront, the agent: 1. **Discovers** available tools by navigating a typed file tree 2. **Generates** TypeScript/Python code that imports and calls typed wrapper functions 3. **Executes** the code in a sandboxed environment 4. **Returns** only filtered/summarized results to the model This reduces token usage from O(all_tool_definitions) to O(only_relevant_imports). ### File Tree Structure ``` project/ ├── servers/ │ ├── google-drive/ │ │ ├── getDocument.ts │ │ ├── getSheet.ts │ │ └── index.ts # Re-exports all tools │ ├── salesforce/ │ │ └── index.ts │ └── slack/ │ └── index.ts ├── skills/ # Agent-accumulated reusable functions ├── workspace/ # Persistent state between executions ├── client.ts # MCP client that routes calls to servers └── sandbox.config.ts # Execution environment configuration ``` Each MCP tool gets a **typed wrapper** function the agent imports (`callMCPTool<T>("server__tool", input)`); the agent writes ordinary code against those wrappers. See [REFERENCE.md → Typed wrapper pattern](REFERENCE.md#typed-wrapper-pattern). ## Key Patterns Six patterns make this efficient — each with a worked code example in [REFERENCE.md → Key patterns](REFERENCE.md#key-patterns): | Pattern | What it buys | |---------|--------------| | **Progressive tool discovery** | Navigate `servers/` on demand — ~150K tokens → ~2K (98.7% reduction) | | **Context-efficient filtering** | Filter large datasets in the sandbox; only a summary reaches the model | | **Native control flow** | Loops/retries/conditionals run in the sandbox, not as chained tool calls | | **PII tokenization** | The client tokenizes sensitive fields so PII never enters model context | | **State persistence** | Save intermediate results to `workspace/` for cross-execution continuity | | **Skill accumulation** | Persist reusable functions to `skills/` for future executions | ## Scaffolding a New Project The five-step scaffold — identify servers → generate typed wrappers → create the routing client → configure the sandbox → wire the agent loop — is detailed with code in [REFERENCE.md → Scaffolding a new project](REFERENCE.md#scaffolding-a-new-project). The agent loop becomes: explore `servers/` → generate code → execute in sandbox → filtered output returns → decide done or iterate. ## Security Checklist | Item | Status | |------|--------| | Sandboxed execution environment | Required | | Resource limits (CPU, memory, disk) | Required | | Network isolation (MCP servers only) | Required | | Execution timeout | Required | | PII tokenization in MCP client | Recommended for sensitive data | | Audit logging of all executions | Recommended | | Read-only access to `servers/` | Recommended | | Scoped write access to `workspace/` only | Recommended | ## Quick Reference ### Token Impact | Approach | Tool definitions | Intermediate data | Total | |----------|-----------------|-------------------|-------| | Direct tool calls | All loaded upfront | Passes through context | High | | Code execution | On-demand discovery | Stays in sandbox | Low | ### When NOT to Use This Pattern - Simple integrations with 1–3 MCP servers - All tool responses are small and needed by the model - No sensitive data in tool responses - Infrastructure complexity isn't justified (sandbox setup, monitoring) - Prototype or proof-of-concept stage ## Reference - [REFERENCE.md](REFERENCE.md) — typed-wrapper code, key-pattern examples, scaffolding steps - [Anthropic Engineering: Code Execution with MCP](https://www.anthropic.com/engineering/code-execution-with-mcp) - [Cloudflare "Code Mode"](https://blog.cloudflare.com/) — independent validation of the same pattern
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