
Mcp Server Builder
- 615 installs
- 23.5k repo stars
- Updated July 17, 2026
- alirezarezvani/claude-skills
mcp-server-builder is a Claude agent skill that generates and validates production-ready MCP servers from OpenAPI specs for developers who need typed API tools for Claude, Cursor, or Codex instead of hand-written wrapper
About
mcp-server-builder is an alirezarezvani/claude-skills engineering skill that scaffolds production-ready Model Context Protocol servers from OpenAPI contracts in Python or TypeScript. Two bundled scripts—openapi_to_mcp.py and mcp_validator.py—convert openapi.json paths into tool_manifest.json plus starter server code and run strict structural validation before integration tests. Five reference guides cover OpenAPI extraction, Python and TypeScript server templates, production hardening, and a validation checklist. Developers use mcp-server-builder when exposing internal or external REST APIs to LLM agents, replacing brittle browser automation with typed tools shared across teams. The workflow treats OpenAPI as source of truth, enforces naming and schema quality, and recommends additive-only tool versioning. Reach when bootstrapping MCP integrations from existing API contracts.
- OpenAPI → tool_manifest.json plus Python or TypeScript starter server via openapi_to_mcp.py
- Strict structural validation with mcp_validator.py before you ship tools to agents
- operationId-first tool naming with sanitized method_path fallbacks
- Bundled extraction guide, language templates, and validation checklist references
- Copy-install paths documented for Claude Code, Codex, and OpenClaw skill directories
Mcp Server Builder by the numbers
- 615 all-time installs (skills.sh)
- Ranked #1,545 of 16,565 AI & Agent Building skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Jul 31, 2026 (Skillselion catalog sync)
npx skills add https://github.com/alirezarezvani/claude-skills --skill mcp-server-builderAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 615 |
|---|---|
| repo stars | ★ 23.5k |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 17, 2026 |
| Repository | alirezarezvani/claude-skills ↗ |
How do you generate MCP servers from OpenAPI specs?
Scaffold and validate production-ready MCP servers from an existing OpenAPI spec so your coding agent can call your API safely.
Who is it for?
Developers exposing existing REST APIs as MCP tools who want OpenAPI-driven scaffolds with manifest validation before agent integration.
Skip if: Developers building MCP servers without an OpenAPI contract or who only need one-off browser automation scripts.
When should I use this skill?
User asks to scaffold an MCP server from OpenAPI, validate tool_manifest.json, or expose a REST API to Claude or Cursor agents.
What you get
tool_manifest.json, Python or TypeScript MCP server scaffold, and strict validation report from mcp_validator.py.
- tool_manifest.json
- MCP server scaffold
- Validation report
By the numbers
- Bundles 2 Python scripts: openapi_to_mcp.py and mcp_validator.py
- Includes 5 reference guides for extraction, templates, hardening, and validation
Files
MCP Server Builder
Tier: POWERFUL · Category: Engineering · Domain: AI / API Integration
Overview
Use this skill to design and ship production-ready MCP servers from API contracts instead of hand-written one-off tool wrappers. It focuses on fast scaffolding, schema quality, validation, and safe evolution.
The workflow supports both Python and TypeScript MCP implementations and treats OpenAPI as the source of truth.
Core Capabilities
- Convert OpenAPI paths/operations into MCP tool definitions
- Generate starter server scaffolds (Python or TypeScript)
- Enforce naming, descriptions, and schema consistency
- Validate MCP tool manifests for common production failures
- Apply versioning and backward-compatibility checks
- Separate transport/runtime decisions from tool contract design
When to Use
- You need to expose an internal/external REST API to an LLM agent
- You are replacing brittle browser automation with typed tools
- You want one MCP server shared across teams and assistants
- You need repeatable quality checks before publishing MCP tools
- You want to bootstrap an MCP server from existing OpenAPI specs
Key Workflows
1. OpenAPI to MCP Scaffold
1. Start from a valid OpenAPI spec. 2. Generate tool manifest + starter server code. 3. Review naming and auth strategy. 4. Add endpoint-specific runtime logic.
python3 scripts/openapi_to_mcp.py \
--input openapi.json \
--server-name billing-mcp \
--language python \
--output-dir ./out \
--format textSupports stdin as well:
cat openapi.json | python3 scripts/openapi_to_mcp.py --server-name billing-mcp --language typescript2. Validate MCP Tool Definitions
Run validator before integration tests:
python3 scripts/mcp_validator.py --input out/tool_manifest.json --strict --format textChecks include duplicate names, invalid schema shape, missing descriptions, empty required fields, and naming hygiene.
3. Runtime Selection
- Choose Python for fast iteration and data-heavy backends.
- Choose TypeScript for unified JS stacks and tighter frontend/backend contract reuse.
- Keep tool contracts stable even if transport/runtime changes.
4. Harden for Production
Key items before publishing:
- Keep secrets in env vars, not tool schemas
- Prefer outbound host allowlists over open proxies
- Use additive-only changes; never rename tool names in-place
Full hardening guidance: references/production-hardening-guide.md.
Script Interfaces
python3 scripts/openapi_to_mcp.py --help- Reads OpenAPI from stdin or
--input - Produces manifest + server scaffold
- Emits JSON summary or text report
python3 scripts/mcp_validator.py --help- Validates manifests and optional runtime config
- Returns non-zero exit in strict mode when errors exist
Reference Material
- references/production-hardening-guide.md — auth & safety design, versioning strategy, common pitfalls, best practices, architecture decisions, contract quality gates, testing strategy, deployment practices, security controls
- references/openapi-extraction-guide.md
- references/python-server-template.md
- references/typescript-server-template.md
- references/validation-checklist.md
- README.md
MCP Server Builder
Generate and validate MCP servers from OpenAPI contracts with production-focused tooling. This skill helps teams bootstrap fast and enforce schema quality before shipping.
Quick Start
# Generate scaffold from OpenAPI
python3 scripts/openapi_to_mcp.py \
--input openapi.json \
--server-name my-mcp \
--language python \
--output-dir ./generated \
--format text
# Validate generated manifest
python3 scripts/mcp_validator.py --input generated/tool_manifest.json --strict --format textIncluded Tools
scripts/openapi_to_mcp.py: OpenAPI ->tool_manifest.json+ starter server scaffoldscripts/mcp_validator.py: structural and quality validation for MCP tool definitions
References
references/openapi-extraction-guide.mdreferences/python-server-template.mdreferences/typescript-server-template.mdreferences/validation-checklist.md
Installation
Claude Code
cp -R engineering/mcp-server-builder ~/.claude/skills/mcp-server-builderOpenAI Codex
cp -R engineering/mcp-server-builder ~/.codex/skills/mcp-server-builderOpenClaw
cp -R engineering/mcp-server-builder ~/.openclaw/skills/mcp-server-builderOpenAPI Extraction Guide
Goal
Turn stable API operations into stable MCP tools with clear names and reliable schemas.
Extraction Rules
1. Prefer operationId as tool name. 2. Fallback naming: <method>_<path> sanitized to snake_case. 3. Pull summary for tool description; fallback to description. 4. Merge path/query parameters into inputSchema.properties. 5. Merge application/json request-body object properties when available. 6. Preserve required fields from both parameters and request body.
Naming Guidance
Good names:
list_customerscreate_invoicearchive_project
Avoid:
tool1runget__v1__customer___id
Schema Guidance
inputSchema.typemust beobject.- Every
requiredkey must exist inproperties. - Include concise descriptions on high-risk fields (IDs, dates, money, destructive flags).
Production Hardening Guide — Safety, Versioning, Quality Gates
The advisory layer behind the mcp-server-builder workflows: read this when hardening a scaffolded server for production, designing auth, planning contract evolution, or reviewing a manifest before publishing.
Auth & Safety Design
- Keep secrets in env, not in tool schemas.
- Prefer explicit allowlists for outbound hosts.
- Return structured errors (
code,message,details) for agent recovery. - Avoid destructive operations without explicit confirmation inputs.
Versioning Strategy
- Additive fields only for non-breaking updates.
- Never rename tool names in-place.
- Introduce new tool IDs for breaking behavior changes.
- Maintain changelog of tool contracts per release.
Common Pitfalls
1. Tool names derived directly from raw paths (get__v1__users___id) 2. Missing operation descriptions (agents choose tools poorly) 3. Ambiguous parameter schemas with no required fields 4. Mixing transport errors and domain errors in one opaque message 5. Building tool contracts that expose secret values 6. Breaking clients by changing schema keys without versioning
Best Practices
1. Use operationId as canonical tool name when available. 2. Keep one task intent per tool; avoid mega-tools. 3. Add concise descriptions with action verbs. 4. Validate contracts in CI using strict mode. 5. Keep generated scaffold committed, then customize incrementally. 6. Pair contract changes with changelog entries.
Architecture Decisions
Choose the server approach per constraint:
- Python runtime: faster iteration, data pipelines, backend-heavy teams
- TypeScript runtime: shared types with JS stack, frontend-heavy teams
- Single MCP server: easiest operations, broader blast radius
- Split domain servers: cleaner ownership and safer change boundaries
Contract Quality Gates
Before publishing a manifest:
1. Every tool has clear verb-first name. 2. Every tool description explains intent and expected result. 3. Every required field is explicitly typed. 4. Destructive actions include confirmation parameters. 5. Error payload format is consistent across all tools. 6. Validator returns zero errors in strict mode.
Testing Strategy
- Unit: validate transformation from OpenAPI operation to MCP tool schema.
- Contract: snapshot
tool_manifest.jsonand review diffs in PR. - Integration: call generated tool handlers against staging API.
- Resilience: simulate 4xx/5xx upstream errors and verify structured responses.
Deployment Practices
- Pin MCP runtime dependencies per environment.
- Roll out server updates behind versioned endpoint/process.
- Keep backward compatibility for one release window minimum.
- Add changelog notes for new/removed/changed tool contracts.
Security Controls
- Keep outbound host allowlist explicit.
- Do not proxy arbitrary URLs from user-provided input.
- Redact secrets and auth headers from logs.
- Rate-limit high-cost tools and add request timeouts.
Python MCP Server Template
from fastmcp import FastMCP
import httpx
import os
mcp = FastMCP(name="my-server")
API_BASE = os.environ["API_BASE"]
API_TOKEN = os.environ["API_TOKEN"]
@mcp.tool()
def list_items(input: dict) -> dict:
with httpx.Client(base_url=API_BASE, headers={"Authorization": f"Bearer {API_TOKEN}"}) as client:
resp = client.get("/items", params=input)
if resp.status_code >= 400:
return {"error": {"code": "upstream_error", "message": "List failed", "details": resp.text}}
return resp.json()
if __name__ == "__main__":
mcp.run()TypeScript MCP Server Template
import { FastMCP } from "fastmcp";
const server = new FastMCP({ name: "my-server" });
server.tool(
"list_items",
"List items from upstream service",
async (input) => {
return {
content: [{ type: "text", text: JSON.stringify({ status: "todo", input }) }],
};
}
);
server.run();MCP Validation Checklist
Structural Integrity
- [ ] Tool names are unique across the manifest
- [ ] Tool names use lowercase snake_case (3-64 chars,
[a-z0-9_]) - [ ]
inputSchema.typeis always"object" - [ ] Every
requiredfield exists inproperties - [ ] No empty
propertiesobjects (warn if inputs truly optional)
Descriptive Quality
- [ ] All tools include actionable descriptions (≥10 chars)
- [ ] Descriptions start with a verb ("Create…", "Retrieve…", "Delete…")
- [ ] Parameter descriptions explain expected values, not just types
Security & Safety
- [ ] Auth tokens and secrets are NOT exposed in tool schemas
- [ ] Destructive tools require explicit confirmation input parameters
- [ ] No tool accepts arbitrary URLs or file paths without validation
- [ ] Outbound host allowlists are explicit where applicable
Versioning & Compatibility
- [ ] Breaking tool changes use new tool IDs (never rename in-place)
- [ ] Additive-only changes for non-breaking updates
- [ ] Contract changelog is maintained per release
- [ ] Deprecated tools include sunset timeline in description
Runtime & Error Handling
- [ ] Error responses use consistent structure (
code,message,details) - [ ] Timeout and rate-limit behaviors are documented
- [ ] Large response payloads are paginated or truncated
#!/usr/bin/env python3
"""Validate MCP tool manifest files for common contract issues.
Input sources:
- --input <manifest.json>
- stdin JSON
Validation domains:
- structural correctness
- naming hygiene
- schema consistency
- descriptive completeness
"""
import argparse
import json
import re
import sys
from dataclasses import dataclass, asdict
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
TOOL_NAME_RE = re.compile(r"^[a-z0-9_]{3,64}$")
class CLIError(Exception):
"""Raised for expected CLI failures."""
@dataclass
class ValidationResult:
errors: List[str]
warnings: List[str]
tool_count: int
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Validate MCP tool definitions.")
parser.add_argument("--input", help="Path to manifest JSON file. If omitted, reads from stdin.")
parser.add_argument("--strict", action="store_true", help="Exit non-zero when errors are found.")
parser.add_argument("--format", choices=["text", "json"], default="text", help="Output format.")
return parser.parse_args()
def load_manifest(input_path: Optional[str]) -> Dict[str, Any]:
if input_path:
try:
data = Path(input_path).read_text(encoding="utf-8")
except Exception as exc:
raise CLIError(f"Failed reading --input: {exc}") from exc
else:
if sys.stdin.isatty():
raise CLIError("No input provided. Use --input or pipe manifest JSON via stdin.")
data = sys.stdin.read().strip()
if not data:
raise CLIError("Empty stdin.")
try:
payload = json.loads(data)
except json.JSONDecodeError as exc:
raise CLIError(f"Invalid JSON input: {exc}") from exc
if not isinstance(payload, dict):
raise CLIError("Manifest root must be a JSON object.")
return payload
def validate_schema(tool_name: str, schema: Dict[str, Any]) -> Tuple[List[str], List[str]]:
errors: List[str] = []
warnings: List[str] = []
if schema.get("type") != "object":
errors.append(f"{tool_name}: inputSchema.type must be 'object'.")
props = schema.get("properties", {})
if not isinstance(props, dict):
errors.append(f"{tool_name}: inputSchema.properties must be an object.")
props = {}
required = schema.get("required", [])
if not isinstance(required, list):
errors.append(f"{tool_name}: inputSchema.required must be an array.")
required = []
prop_keys = set(props.keys())
for req in required:
if req not in prop_keys:
errors.append(f"{tool_name}: required field '{req}' is not defined in properties.")
if not props:
warnings.append(f"{tool_name}: no input properties declared.")
for pname, pdef in props.items():
if not isinstance(pdef, dict):
errors.append(f"{tool_name}: property '{pname}' must be an object.")
continue
ptype = pdef.get("type")
if not ptype:
warnings.append(f"{tool_name}: property '{pname}' has no explicit type.")
return errors, warnings
def validate_manifest(payload: Dict[str, Any]) -> ValidationResult:
errors: List[str] = []
warnings: List[str] = []
tools = payload.get("tools")
if not isinstance(tools, list):
raise CLIError("Manifest must include a 'tools' array.")
seen_names = set()
for idx, tool in enumerate(tools):
if not isinstance(tool, dict):
errors.append(f"tool[{idx}] is not an object.")
continue
name = str(tool.get("name", "")).strip()
desc = str(tool.get("description", "")).strip()
schema = tool.get("inputSchema")
if not name:
errors.append(f"tool[{idx}] missing name.")
continue
if name in seen_names:
errors.append(f"duplicate tool name: {name}")
seen_names.add(name)
if not TOOL_NAME_RE.match(name):
warnings.append(
f"{name}: non-standard naming; prefer lowercase snake_case (3-64 chars, [a-z0-9_])."
)
if len(desc) < 10:
warnings.append(f"{name}: description too short; provide actionable purpose.")
if not isinstance(schema, dict):
errors.append(f"{name}: missing or invalid inputSchema object.")
continue
schema_errors, schema_warnings = validate_schema(name, schema)
errors.extend(schema_errors)
warnings.extend(schema_warnings)
return ValidationResult(errors=errors, warnings=warnings, tool_count=len(tools))
def to_text(result: ValidationResult) -> str:
lines = [
"MCP manifest validation",
f"- tools: {result.tool_count}",
f"- errors: {len(result.errors)}",
f"- warnings: {len(result.warnings)}",
]
if result.errors:
lines.append("Errors:")
lines.extend([f"- {item}" for item in result.errors])
if result.warnings:
lines.append("Warnings:")
lines.extend([f"- {item}" for item in result.warnings])
return "\n".join(lines)
def main() -> int:
args = parse_args()
payload = load_manifest(args.input)
result = validate_manifest(payload)
if args.format == "json":
print(json.dumps(asdict(result), indent=2))
else:
print(to_text(result))
if args.strict and result.errors:
return 1
return 0
if __name__ == "__main__":
try:
raise SystemExit(main())
except CLIError as exc:
print(f"ERROR: {exc}", file=sys.stderr)
raise SystemExit(2)
#!/usr/bin/env python3
"""Generate MCP scaffold files from an OpenAPI specification.
Input sources:
- --input <file>
- stdin (JSON or YAML when PyYAML is available)
Output:
- tool_manifest.json
- server.py or server.ts scaffold
- summary in text/json
"""
import argparse
import json
import re
import sys
from dataclasses import dataclass, asdict
from pathlib import Path
from typing import Any, Dict, List, Optional
HTTP_METHODS = {"get", "post", "put", "patch", "delete"}
class CLIError(Exception):
"""Raised for expected CLI failures."""
@dataclass
class GenerationSummary:
server_name: str
language: str
operations_total: int
tools_generated: int
output_dir: str
manifest_path: str
scaffold_path: str
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Generate MCP server scaffold from OpenAPI.")
parser.add_argument("--input", help="OpenAPI file path (JSON or YAML). If omitted, reads from stdin.")
parser.add_argument("--server-name", required=True, help="MCP server name.")
parser.add_argument("--language", choices=["python", "typescript"], default="python", help="Scaffold language.")
parser.add_argument("--output-dir", default=".", help="Directory to write generated files.")
parser.add_argument("--format", choices=["text", "json"], default="text", help="Output format.")
return parser.parse_args()
def load_raw_input(input_path: Optional[str]) -> str:
if input_path:
try:
return Path(input_path).read_text(encoding="utf-8")
except Exception as exc:
raise CLIError(f"Failed to read --input file: {exc}") from exc
if sys.stdin.isatty():
raise CLIError("No input provided. Use --input <spec-file> or pipe OpenAPI via stdin.")
data = sys.stdin.read().strip()
if not data:
raise CLIError("Stdin was provided but empty.")
return data
def parse_openapi(raw: str) -> Dict[str, Any]:
try:
return json.loads(raw)
except json.JSONDecodeError:
try:
import yaml # type: ignore
parsed = yaml.safe_load(raw)
if not isinstance(parsed, dict):
raise CLIError("YAML OpenAPI did not parse into an object.")
return parsed
except ImportError as exc:
raise CLIError("Input is not valid JSON and PyYAML is unavailable for YAML parsing.") from exc
except Exception as exc:
raise CLIError(f"Failed to parse OpenAPI input: {exc}") from exc
def sanitize_tool_name(name: str) -> str:
cleaned = re.sub(r"[^a-zA-Z0-9_]+", "_", name).strip("_")
cleaned = re.sub(r"_+", "_", cleaned)
return cleaned.lower() or "unnamed_tool"
def schema_from_parameter(param: Dict[str, Any]) -> Dict[str, Any]:
schema = param.get("schema", {})
if not isinstance(schema, dict):
schema = {}
out = {
"type": schema.get("type", "string"),
"description": param.get("description", ""),
}
if "enum" in schema:
out["enum"] = schema["enum"]
return out
def extract_tools(spec: Dict[str, Any]) -> List[Dict[str, Any]]:
paths = spec.get("paths", {})
if not isinstance(paths, dict):
raise CLIError("OpenAPI spec missing valid 'paths' object.")
tools = []
for path, methods in paths.items():
if not isinstance(methods, dict):
continue
for method, operation in methods.items():
method_l = str(method).lower()
if method_l not in HTTP_METHODS or not isinstance(operation, dict):
continue
op_id = operation.get("operationId")
if op_id:
name = sanitize_tool_name(str(op_id))
else:
name = sanitize_tool_name(f"{method_l}_{path}")
description = str(operation.get("summary") or operation.get("description") or f"{method_l.upper()} {path}")
properties: Dict[str, Any] = {}
required: List[str] = []
for param in operation.get("parameters", []):
if not isinstance(param, dict):
continue
pname = str(param.get("name", "")).strip()
if not pname:
continue
properties[pname] = schema_from_parameter(param)
if bool(param.get("required")):
required.append(pname)
request_body = operation.get("requestBody", {})
if isinstance(request_body, dict):
content = request_body.get("content", {})
if isinstance(content, dict):
app_json = content.get("application/json", {})
if isinstance(app_json, dict):
schema = app_json.get("schema", {})
if isinstance(schema, dict) and schema.get("type") == "object":
rb_props = schema.get("properties", {})
if isinstance(rb_props, dict):
for key, val in rb_props.items():
if isinstance(val, dict):
properties[key] = val
rb_required = schema.get("required", [])
if isinstance(rb_required, list):
required.extend([str(x) for x in rb_required])
tool = {
"name": name,
"description": description,
"inputSchema": {
"type": "object",
"properties": properties,
"required": sorted(set(required)),
},
"x-openapi": {"path": path, "method": method_l},
}
tools.append(tool)
return tools
def python_scaffold(server_name: str, tools: List[Dict[str, Any]]) -> str:
handlers = []
for tool in tools:
fname = sanitize_tool_name(tool["name"])
handlers.append(
f"@mcp.tool()\ndef {fname}(input: dict) -> dict:\n"
f" \"\"\"{tool['description']}\"\"\"\n"
f" return {{\"tool\": \"{tool['name']}\", \"status\": \"todo\", \"input\": input}}\n"
)
return "\n".join(
[
"#!/usr/bin/env python3",
'"""Generated MCP server scaffold."""',
"",
"from fastmcp import FastMCP",
"",
f"mcp = FastMCP(name={server_name!r})",
"",
*handlers,
"",
"if __name__ == '__main__':",
" mcp.run()",
"",
]
)
def typescript_scaffold(server_name: str, tools: List[Dict[str, Any]]) -> str:
registrations = []
for tool in tools:
const_name = sanitize_tool_name(tool["name"])
registrations.append(
"server.tool(\n"
f" '{tool['name']}',\n"
f" '{tool['description']}',\n"
" async (input) => ({\n"
f" content: [{{ type: 'text', text: JSON.stringify({{ tool: '{const_name}', status: 'todo', input }}) }}],\n"
" })\n"
");"
)
return "\n".join(
[
"// Generated MCP server scaffold",
"import { FastMCP } from 'fastmcp';",
"",
f"const server = new FastMCP({{ name: '{server_name}' }});",
"",
*registrations,
"",
"server.run();",
"",
]
)
def write_outputs(server_name: str, language: str, output_dir: Path, tools: List[Dict[str, Any]]) -> GenerationSummary:
output_dir.mkdir(parents=True, exist_ok=True)
manifest_path = output_dir / "tool_manifest.json"
manifest = {"server": server_name, "tools": tools}
manifest_path.write_text(json.dumps(manifest, indent=2), encoding="utf-8")
if language == "python":
scaffold_path = output_dir / "server.py"
scaffold_path.write_text(python_scaffold(server_name, tools), encoding="utf-8")
else:
scaffold_path = output_dir / "server.ts"
scaffold_path.write_text(typescript_scaffold(server_name, tools), encoding="utf-8")
return GenerationSummary(
server_name=server_name,
language=language,
operations_total=len(tools),
tools_generated=len(tools),
output_dir=str(output_dir.resolve()),
manifest_path=str(manifest_path.resolve()),
scaffold_path=str(scaffold_path.resolve()),
)
def main() -> int:
args = parse_args()
raw = load_raw_input(args.input)
spec = parse_openapi(raw)
tools = extract_tools(spec)
if not tools:
raise CLIError("No operations discovered in OpenAPI paths.")
summary = write_outputs(
server_name=args.server_name,
language=args.language,
output_dir=Path(args.output_dir),
tools=tools,
)
if args.format == "json":
print(json.dumps(asdict(summary), indent=2))
else:
print("MCP scaffold generated")
print(f"- server: {summary.server_name}")
print(f"- language: {summary.language}")
print(f"- tools: {summary.tools_generated}")
print(f"- manifest: {summary.manifest_path}")
print(f"- scaffold: {summary.scaffold_path}")
return 0
if __name__ == "__main__":
try:
raise SystemExit(main())
except CLIError as exc:
print(f"ERROR: {exc}", file=sys.stderr)
raise SystemExit(2)
Related skills
How it compares
Pick mcp-server-builder over manual MCP tutorials when you already have openapi.json and need repeatable scaffold plus strict manifest validation.
FAQ
Which scripts does mcp-server-builder include?
mcp-server-builder bundles openapi_to_mcp.py for OpenAPI-to-MCP scaffold generation and mcp_validator.py for strict tool_manifest.json validation checking duplicate names, schema shape, and missing descriptions.
What languages does mcp-server-builder support?
mcp-server-builder generates Python or TypeScript MCP server scaffolds via openapi_to_mcp.py --language python or --language typescript, with separate reference templates for each runtime.
How do you validate MCP tools before integration tests?
mcp-server-builder runs python3 scripts/mcp_validator.py --input out/tool_manifest.json --strict --format text to catch duplicate tool names, invalid schemas, and empty required fields before agent integration.
Is Mcp Server Builder safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.