Twelve Data MCP Server

Instructions

Implementation Reference

• src/mcp_server_twelve_data/server.py:44-84 (handler)

  Generic handler function used by all generated endpoint tools, including GetIpoCalendar. Resolves path parameters, injects API key, makes HTTP GET request to Twelve Data API, handles errors, and validates response with Pydantic model.
  async def _call_endpoint( endpoint: str, params: P, response_model: Type[R], ctx: Context ) -> R: params.apikey = extract_twelve_data_apikey( twelve_data_apikey=twelve_data_apikey, transport=transport, ctx=ctx ) params_dict = params.model_dump(exclude_none=True) resolved_endpoint = resolve_path_params(endpoint, params_dict) async with httpx.AsyncClient( trust_env=False, headers={ "accept": "application/json", "user-agent": "python-httpx/0.24.0" }, ) as client: resp = await client.get( f"{api_base}/{resolved_endpoint}", params=params_dict ) resp.raise_for_status() resp_json = resp.json() if isinstance(resp_json, dict): status = resp_json.get("status") if status == "error": code = resp_json.get('code') raise HTTPException( status_code=code, detail=f"Failed to perform request," f" code = {code}, message = {resp_json.get('message')}" ) return response_model.model_validate(resp_json)
• src/mcp_server_twelve_data/server.py:88-88 (registration)

  Registers all Twelve Data API endpoint tools, including GetIpoCalendar, by calling the generated register_all_tools function.
  register_all_tools(server=server, _call_endpoint=_call_endpoint)
• src/mcp_server_twelve_data/server.py:124-124 (registration)

  Alternative registration point for tools when no U-tool or doc-tool features are enabled, includes GetIpoCalendar.
  register_all_tools(server=server, _call_endpoint=_call_endpoint)
• scripts/generate_requests_models.py:132-242 (schema)

  Script that generates Pydantic BaseModel input schemas (e.g., GetIpoCalendarRequest) for all API operations from the OpenAPI spec.
  def main(): # Load the OpenAPI specification with open(OPENAPI_PATH, "r", encoding="utf-8") as f: spec = json.load(f) components = spec.get("components", {}).get("schemas", {}) request_models: List[str] = [] request_names: set = set() for path, methods in spec.get("paths", {}).items(): for http_method, op in methods.items(): opid = op.get("operationId") if not opid: continue class_name = canonical_class_name(opid, "Request") # Collect parameters from path, query, header, etc. props: dict = {} for param in op.get("parameters", []): name = param["name"] sch = param.get("schema", {"type": "string"}) typ = python_type(sch, components) required = param.get("required", False) desc = param.get("description") or sch.get("description") examples = collect_examples(param, sch) default = sch.get("default", None) props[name] = { "type": typ, "required": required, "description": desc, "examples": examples, "default": default, } # Collect JSON body properties body = op.get("requestBody", {}) \ .get("content", {}) \ .get("application/json", {}) \ .get("schema") if body: body_sch = resolve_schema(body, components) for name, sch in body_sch.get("properties", {}).items(): typ = python_type(sch, components) required = name in body_sch.get("required", []) desc = sch.get("description") examples = collect_examples({}, sch) default = sch.get("default", None) props[name] = { "type": typ, "required": required, "description": desc, "examples": examples, "default": default, } if "outputsize" not in props: props["outputsize"] = { "type": "int", "required": False, "description": ( "Number of data points to retrieve. Supports values in the range from `1` to `5000`. " "Default `10` when no date parameters are set, otherwise set to maximum" ), "examples": [10], "default": 10, } else: props["outputsize"]["default"] = 10 props["outputsize"]["description"] = props["outputsize"]["description"].replace( 'Default `30`', 'Default `10`' ) props["outputsize"]["examples"] = [10] # Add apikey with default="demo" props["apikey"] = { "type": "str", "required": False, "description": "API key", "examples": ["demo"], "default": "demo", } if "interval" in props: props["interval"]["required"] = False props["interval"]["default"] = "1day" # Append plan availability to the description if x-starting-plan is present starting_plan = op.get("x-starting-plan") description = op.get("description", "") if starting_plan: addon = f" Available starting from the `{starting_plan}` plan." description = (description or "") + addon code = gen_class(class_name, props, description) if class_name not in request_names: request_models.append(code) request_names.add(class_name) # Write all generated models to the target file header = ( "from pydantic import BaseModel, Field\n" "from typing import Any, List, Optional\n\n" ) Path(REQUESTS_FILE).write_text(header + "\n\n".join(request_models), encoding="utf-8") print(f"Generated request models: {REQUESTS_FILE}") if __name__ == "__main__": main()
• scripts/generate_tools.py:37-69 (helper)

  Generates the code for tools.py (or tools_autogen.py) which defines the register_all_tools function and thin async def wrappers for each tool (including GetIpoCalendar) that delegate to _call_endpoint.
  def generate_code(ops): def fix_case(name: str) -> str: return name[0].upper() + name[1:] if name.lower().startswith("advanced") else name lines = [ 'from mcp.server import FastMCP', 'from mcp.server.fastmcp import Context', '' ] # Import request models for op, _, _ in ops: lines.append(f'from .request_models import {fix_case(op)}Request') lines.append('') # Import response models for op, _, _ in ops: lines.append(f'from .response_models import {fix_case(op)}200Response') lines.append('') # Register tools lines.append('def register_all_tools(server: FastMCP, _call_endpoint):') for op, desc, key in ops: fixed_op = fix_case(op) lines += [ f' @server.tool(name="{op}",', f' description="{desc}")', f' async def {op}(params: {fixed_op}Request, ctx: Context) -> {fixed_op}200Response:', f' return await _call_endpoint("{key}", params, {fixed_op}200Response, ctx)', '' ] return '\n'.join(lines)