[Bug]: MCP "ask" tool exposes an empty parameters schema ({"type":"object"} with no "properties"), rejected by strict tool-calling clients

crawl4ai version

0.9.2

Expected Behavior

Every MCP tool exposed by the mcp server should publish a valid JSON-Schema for its parameters. For an object-type schema that means including a properties key (even if empty). Strict OpenAI-compatible tool-calling clients require parameters.properties to be present, otherwise the fail to load.

Current Behavior

The ask MCP tool publishes a parameters schema of exactly:

{ "type": "object" }

with no properties key. Strict validators reject it. LM Studio or LibreChat, for example, returns a 400 before the request even runs:

400 [{"code":"invalid_type","expected":"object","received":"undefined",
      "path":[<n>,"function","parameters","properties"],"message":"Required"}]

Every other MCP tool (md, html, screenshot, pdf, crawl) works, because they are POST endpoints backed by a Pydantic body model and therefore get a fully-populated properties schema. ask is the only tool defined as @app.get("/ask") using FastAPI Query(...) params (context_type, query, score_ratio, max_results). The MCP bridge appears to derive the input schema from the Pydantic request body only, so a query-parameter endpoint yields an empty object schema. Net effect: the ask tool is unusable with any MCP client that strictly validates tool schemas, and there is no config/env flag to disable just that tool (attach_mcp registers all @mcp_tool endpoints unconditionally).

Is this reproducible?

Yes

Inputs Causing the Bug

- Any OpenAI-compatible MCP client that validates tool JSON-Schemas (e.g. LM Studio)
- Tool: ask  (function name "ask_mcp_crawl4ai" in clients)
- Server: official Crawl4AI Docker deployment, MCP over /mcp/sse (or HTTP)

Steps to Reproduce

1. Run the Crawl4AI Docker server (0.9.2) with the MCP endpoint enabled.
2. GET /mcp/schema and inspect the "ask" tool — its parameters are {"type":"object"} with no "properties".
3. Connect a strict OpenAI-compatible client (LM Studio, Librechat) to the MCP endpoint, enabling the crawl4ai tools.
4. Send any chat completion that includes the tool list.
5. Observe a 400: parameters.properties "Required" for the ask tool; the request never runs.

Code snippets

Not applicable

OS

Linux (official Crawl4AI Docker image)

Python version

unclecode/crawl4ai:0.9.2 image (Python 3.x)

Browser

N/A

Browser version

N/A

Error logs & Screenshots (if applicable)

No response

Start at the @app.get("/ask") endpoint and the attach_mcp registration path, then inspect the /mcp/schema output for the ask tool. Ensure its object parameters schema includes a properties key while preserving context_type, query, score_ratio, and max_results, and verify that strict MCP clients accept the generated schema.