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/mcp-scripting

Write mcpScript JavaScript for discovering, inspecting, and calling MCP tools.

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pi-mcp-adapter
1.5k1 skill
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$ npx -y skills add nicobailon/pi-mcp-adapter --skill mcp-scripting --agent claude-code

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  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/mcp-scripting

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Write mcpScript JavaScript for discovering, inspecting, and calling MCP tools.

SKILL.md

mcp-scripting.SKILL.md
name: mcp-scripting
description: Write mcpScript JavaScript for discovering, inspecting, and calling MCP tools.
disable-model-invocation: true

MCP scripting

For multi-call MCP work, write ordinary JavaScript with loops, filtering, chaining, fan-out, or other logic between calls. Run that source with `mcpScript`; it is the primary MCP orchestration surface. For a single MCP search, describe, status check, auth action, or tool call, use `mcp` instead.

Write the source naturally, then pass it as `mcpScript`'s `code` argument:

const { items } = await tools.search({ query: "search issues", server: "github" });
const candidate = items[0];
if (!candidate) return { error: "No matching tool" };

const details = await tools.describe({ path: candidate.path });
if (details.error) return details;

const result = await tools.call(details.path, { query: "is:open label:bug" });
if (!result.ok) return result;
emit({ tool: details.path, completed: true });
return result.data;

Workflow

1. Find candidate tools with `await tools.search({ query, server?, limit?, offset? })`. 2. Inspect the exact returned path with `await tools.describe({ path })`. 3. Call it with `tools.call(path, args)`.

Descriptors include `inputTypeScript` (a compact parameter shape, or formatted schema fallback). When a compact shape would omit documented fields, `inputGuidance` preserves their descriptions, including formats and units. Undocumented inputs stay compact.

When advertised by the server, `outputSchema` is the original JSON Schema and `outputSchemaTarget` is `"data.structuredContent"`: it describes structured output inside the successful `{ ok: true, data }` call envelope, not the envelope itself. Inspect this schema for result fields and constraints; unsupported constructs remain intact rather than being presented as an approximate TypeScript type. Both output fields are absent when no output schema is advertised. Discovery and cache refresh preserve these optional schemas; old cache entries gain them on the next server metadata refresh. Ordinary search results do not include schemas.

Calls resolve to `{ ok: true, data }` or `{ ok: false, error }`; handle failed calls instead of expecting them to stop the script. `emit(value)` adds user-visible output before the final `return` value. `console` output is captured too.

On success, `data` may still be the raw MCP `CallToolResult` envelope rather than the domain payload. Check `data.structuredContent` for the fields your script expects; if they are absent, inspect text blocks in `data.content` too (some servers emit newline-delimited JSON). If neither shape is understood, return or emit the envelope for inspection instead of coercing it to `[]` or `{}`.

`tools` is a non-enumerable proxy: `Object.keys(tools)` throws. Always use `tools.search` for discovery. When a known flat path is a valid identifier, direct calls such as `tools.github_search_issues(args)` are supported; use bracket syntax for hyphenated names: `tools["server_tool-name"](args)`. `search`, `call`, `describe`, and promise/serialization names (`then`, `catch`, `finally`, `toJSON`, `toString`, `valueOf`) are reserved on the proxy; if a flat path collides with one, call it via `tools.call("exact-path", args)`.

Successful intermediate data bypasses presentation truncation, summarization, and artifact spill until the script emits, logs, or returns it. A fixed, non-configurable **16 MiB cumulative UTF-8 JSON transfer budget per script** covers sequential and parallel calls. A result exceeding the remaining budget returns `{ ok: false, error: { code: "intermediate_result_too_large", message } }` with a failed call trace; rejected calls do not consume the budget, but upstream side effects may already have happened. Resource calls retain transformed text or `"(empty resource)"`; emitted, logged, or returned output and ordinary MCP calls remain guarded. This is not a memory limit: responses, serialization, copies, concurrency, and script values still allocate memory, and synchronous serialization can delay deadline handling.

`tools.search` and `tools.describe` are asynchronous and must be awaited. The default script timeout is 30 seconds; the worker is terminated at the deadline, including for infinite loops. Every invocation still uses normal lazy connection, authentication, and approval gates. Result details contain a concise `calls` trace with every search, describe, and call operation; each entry includes its query or path, outcome, and duration.

Use plain JavaScript loops and Promise utilities for composition. Fluent helpers such as `tools.find(...).one()`, `tools.parallel(...)`, and `tools.retry(...)` are not provided.

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MIT
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Repo: nicobailon/pi-mcp-adapter