api_docs
Search and fetch official API documentation with examples and explanations for any API by dynamically discovering documentation sources.
Instructions
Search and fetch official API documentation with examples and explanations.
Documentation-first approach: fetches human-written docs with context, examples,
and best practices. Much more useful than OpenAPI specs alone.
Discovery strategy:
1. Try common URL patterns (docs.{api}.com, {api}.com/docs, etc.)
2. If patterns fail, search for "{api} API official documentation"
3. Crawl discovered docs and extract relevant content
No hardcoded URLs - works for ANY API by discovering docs dynamically.
Examples:
- api_docs("stripe", "create customer", reasoning="Setting up payments")
- api_docs("github", "create repository", reasoning="Automating repo creation")
- api_docs("spartan", "button component", reasoning="Learning UI library")Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| api_name | Yes | ||
| reasoning | Yes | ||
| topic | Yes | ||
| max_results | No |
Implementation Reference
- src/searxng_mcp/server.py:954-1193 (handler)The core handler function for the 'api_docs' MCP tool. Orchestrates finding API docs URL, searching specific topics, crawling relevant pages, and extracting structured information (overview, params, examples, etc.). Uses helper classes from api_docs.py.
async def api_docs( api_name: Annotated[str, "API name (e.g., 'stripe', 'github') or base docs URL"], reasoning: Annotated[str, "Why you're looking up this API (required for analytics)"], topic: Annotated[ str, "What to search for (e.g., 'create customer', 'webhooks', 'authentication')", ], max_results: Annotated[int, "Number of doc pages to fetch (1-3)"] = 2, ) -> str: """ Search and fetch official API documentation with examples and explanations. Documentation-first approach: fetches human-written docs with context, examples, and best practices. Much more useful than OpenAPI specs alone. Discovery strategy: 1. Try common URL patterns (docs.{api}.com, {api}.com/docs, etc.) 2. If patterns fail, search for "{api} API official documentation" 3. Crawl discovered docs and extract relevant content No hardcoded URLs - works for ANY API by discovering docs dynamically. Examples: - api_docs("stripe", "create customer", reasoning="Setting up payments") - api_docs("github", "create repository", reasoning="Automating repo creation") - api_docs("spartan", "button component", reasoning="Learning UI library") """ start_time = time.time() success = False error_msg = None result = "" docs_url = None try: max_results = max(1, min(max_results, 3)) # Clamp to 1-3 # Get alternative search terms for the API search_terms = api_docs_detector.get_search_terms(api_name) # Find documentation URL docs_url = await api_docs_detector.find_docs_url(api_name) if not docs_url: # Fallback: Search for official docs using multiple search terms for search_term in search_terms: search_results = await searcher.search( f"{search_term} official documentation", category="general", max_results=5, ) # Filter for docs-like URLs for hit in search_results: if any( indicator in hit.url.lower() for indicator in ["docs", "developer", "api", "reference"] ): docs_url = hit.url # Extract base URL (remove path beyond /docs or /api) if "/docs" in docs_url: docs_url = docs_url.split("/docs")[0] + "/docs" elif "/api" in docs_url: docs_url = docs_url.split("/api")[0] + "/api" break if docs_url: break if not docs_url: result = ( f"Could not find official documentation for '{api_name}'.\n\n" f"Try:\n" f"- Checking the API name spelling\n" f"- Providing the docs URL directly (e.g., 'https://docs.example.com')\n" f"- Using web_search to find the documentation manually" ) error_msg = "Documentation URL not found" success = False else: # Get the domain for site-specific search docs_domain = api_docs_detector.get_docs_domain(docs_url) # Search within the docs site search_query = f"site:{docs_domain} {topic}" doc_results = await searcher.search( search_query, category="general", max_results=max_results * 2 ) # Fallback 1: If site-specific search fails, try broader search with API name + topic if not doc_results: # Try searching with the API name + topic directly for search_term in search_terms[:2]: # Try first 2 terms doc_results = await searcher.search( f"{search_term} {topic}", category="it", max_results=max_results * 2, ) if doc_results: break # Fallback 2: Try without site restriction but filter results if not doc_results: doc_results = await searcher.search( f"{api_name} API {topic} documentation", category="general", max_results=max_results * 2, ) # Fallback 3: Simplify the topic (extract key terms) and try again if not doc_results and len(topic.split()) > 3: # Extract key terms from complex topics # e.g., "v3 audio tags SSML break tags emotional delivery" -> "audio SSML" import re as re_module # Remove version numbers, common filler words simplified = re_module.sub(r"\bv\d+\b", "", topic, flags=re_module.IGNORECASE) simplified = re_module.sub( r"\b(api|the|a|an|and|or|for|to|with|using)\b", "", simplified, flags=re_module.IGNORECASE, ) key_terms = [w for w in simplified.split() if len(w) > 2][:3] if key_terms: simplified_topic = " ".join(key_terms) doc_results = await searcher.search( f"{api_name} {simplified_topic}", category="it", max_results=max_results * 2, ) # Fallback 4: If all searches fail, try crawling the base docs URL directly if not doc_results and docs_url: try: # Crawl the base docs URL - it often has navigation/overview base_content = await crawler_client.fetch(docs_url, max_chars=15000) if base_content and len(base_content) > 200: # Create a minimal result from the base docs doc = APIDocumentation( api_name=api_name, topic=topic, docs_url=docs_url, overview=api_docs_extractor.extract_overview(base_content), parameters=[], examples=api_docs_extractor.extract_examples(base_content), related_links=api_docs_extractor.extract_links(base_content, docs_url), notes=[ f"Note: Could not find specific docs for '{topic}'. Showing general documentation." ], source_urls=[docs_url], ) result = api_docs_extractor.format_documentation(doc) result = clamp_text(result, MAX_RESPONSE_CHARS) success = True except Exception: # noqa: BLE001 pass # Fall through to error if not doc_results and not success: result = ( f"Found documentation site: {docs_url}\n" f"But no results for topic: '{topic}'\n\n" f"Try:\n" f"- Broader search terms\n" f"- Different wording (e.g., 'customers' instead of 'create customer')\n" f"- Browse the docs directly: {docs_url}" ) error_msg = "No results for topic" success = False elif doc_results: # Crawl the top results source_urls = [] all_content = [] for doc_result in doc_results[:max_results]: try: content = await crawler_client.fetch(doc_result.url, max_chars=12000) all_content.append(content) source_urls.append(doc_result.url) except Exception: # noqa: BLE001 # Skip failed crawls pass if not all_content: result = ( f"Failed to fetch documentation pages. Try browsing directly: {docs_url}" ) error_msg = "Failed to crawl docs" success = False else: # Combine content for extraction combined_content = "\n\n".join(all_content) # Extract structured information overview = api_docs_extractor.extract_overview(combined_content) parameters = api_docs_extractor.extract_parameters(combined_content) examples = api_docs_extractor.extract_examples(combined_content) notes = api_docs_extractor.extract_notes(combined_content) related_links = api_docs_extractor.extract_links(combined_content, docs_url) # Create documentation object doc = APIDocumentation( api_name=api_name, topic=topic, docs_url=docs_url, overview=overview, parameters=parameters, examples=examples, related_links=related_links, notes=notes, source_urls=source_urls, ) # Format and return result = api_docs_extractor.format_documentation(doc) result = clamp_text(result, MAX_RESPONSE_CHARS) success = True except Exception as exc: # noqa: BLE001 error_msg = str(exc) result = f"Failed to fetch API documentation: {exc}\n\nTry using web_search or crawl_url directly." finally: # Track usage response_time = (time.time() - start_time) * 1000 tracker.track_usage( tool_name="api_docs", reasoning=reasoning, parameters={ "api_name": api_name, "topic": topic, "docs_url": docs_url or "not_found", "max_results": max_results, }, response_time_ms=response_time, success=success, error_message=error_msg, response_size=len(result.encode("utf-8")), ) return result - src/searxng_mcp/server.py:954-954 (registration)MCP tool registration decorator for the 'api_docs' tool (name derived from function name).
async def api_docs( - src/searxng_mcp/server.py:955-962 (schema)Input schema defined via Annotated types in the function signature: api_name (str), reasoning (str), topic (str), max_results (int=2).
api_name: Annotated[str, "API name (e.g., 'stripe', 'github') or base docs URL"], reasoning: Annotated[str, "Why you're looking up this API (required for analytics)"], topic: Annotated[ str, "What to search for (e.g., 'create customer', 'webhooks', 'authentication')", ], max_results: Annotated[int, "Number of doc pages to fetch (1-3)"] = 2, ) -> str: - src/searxng_mcp/api_docs.py:27-295 (helper)Helper class to detect and find official API documentation URLs using predefined patterns, aliases for popular APIs, and HTTP validation.
class APIDocsDetector: """Intelligently find API documentation URLs.""" # Common documentation URL patterns to try # Order matters: try most common patterns first (.com before .io) DOC_PATTERNS = [ # .com patterns (most common) "https://docs.{api}.com", "https://{api}.com/docs", "https://{api}.com/docs/api", # Stripe-style "https://www.{api}.com/docs", "https://developers.{api}.com", "https://developer.{api}.com", "https://{api}.com/documentation", "https://api.{api}.com/docs", # Framework-specific patterns "https://{api}.dev", # Vite, Nuxt, etc. "https://www.{api}.dev", "https://{api}.ng", # Angular-based (Spartan) "https://www.{api}.ng", # .io patterns (less common, try after .com) "https://docs.{api}.io", "https://{api}.io/docs", "https://www.{api}.io/docs", # .org patterns "https://{api}.org/docs", "https://www.{api}.org/docs", "https://docs.{api}.org", # .ai patterns "https://docs.{api}.ai", "https://{api}.ai/docs", ] # API name aliases - map common variations to canonical names/URLs # This handles cases like "Meta Graph API" -> "facebook" API_ALIASES: dict[str, str | dict] = { # Meta/Facebook "meta": "facebook", "meta graph": "facebook", "meta graph api": "facebook", "facebook graph": "facebook", "facebook graph api": "facebook", "instagram api": "facebook", "instagram graph": "facebook", # Google "google site verification": { "name": "google", "docs_url": "https://developers.google.com/site-verification", }, "google site verification api": { "name": "google", "docs_url": "https://developers.google.com/site-verification", }, "google analytics": { "name": "google", "docs_url": "https://developers.google.com/analytics", }, "google analytics 4": { "name": "google", "docs_url": "https://developers.google.com/analytics/devguides/config/admin/v1", }, "ga4": { "name": "google", "docs_url": "https://developers.google.com/analytics/devguides/config/admin/v1", }, "gemini": {"name": "google", "docs_url": "https://ai.google.dev/docs"}, "google gemini": {"name": "google", "docs_url": "https://ai.google.dev/docs"}, "vertex ai": {"name": "google", "docs_url": "https://cloud.google.com/vertex-ai/docs"}, "google cloud": {"name": "google", "docs_url": "https://cloud.google.com/docs"}, # TikTok "tiktok": {"name": "tiktok", "docs_url": "https://developers.tiktok.com/doc"}, "tiktok business": { "name": "tiktok", "docs_url": "https://business-api.tiktok.com/portal/docs", }, "tiktok business api": { "name": "tiktok", "docs_url": "https://business-api.tiktok.com/portal/docs", }, "tiktok ads": {"name": "tiktok", "docs_url": "https://business-api.tiktok.com/portal/docs"}, # OpenAI "openai": {"name": "openai", "docs_url": "https://platform.openai.com/docs"}, "chatgpt": {"name": "openai", "docs_url": "https://platform.openai.com/docs"}, "gpt": {"name": "openai", "docs_url": "https://platform.openai.com/docs"}, "dall-e": {"name": "openai", "docs_url": "https://platform.openai.com/docs/guides/images"}, "dalle": {"name": "openai", "docs_url": "https://platform.openai.com/docs/guides/images"}, # Anthropic "anthropic": {"name": "anthropic", "docs_url": "https://docs.anthropic.com"}, "claude": {"name": "anthropic", "docs_url": "https://docs.anthropic.com"}, "claude api": {"name": "anthropic", "docs_url": "https://docs.anthropic.com"}, # Notion "notion": {"name": "notion", "docs_url": "https://developers.notion.com"}, "notion api": {"name": "notion", "docs_url": "https://developers.notion.com/reference"}, # Slack "slack": {"name": "slack", "docs_url": "https://api.slack.com/docs"}, "slack api": {"name": "slack", "docs_url": "https://api.slack.com/docs"}, "slack block kit": {"name": "slack", "docs_url": "https://api.slack.com/block-kit"}, # ElevenLabs "elevenlabs": {"name": "elevenlabs", "docs_url": "https://elevenlabs.io/docs"}, "eleven labs": {"name": "elevenlabs", "docs_url": "https://elevenlabs.io/docs"}, "11labs": {"name": "elevenlabs", "docs_url": "https://elevenlabs.io/docs"}, # Fal.ai "fal": {"name": "fal", "docs_url": "https://fal.ai/docs"}, "fal.ai": {"name": "fal", "docs_url": "https://fal.ai/docs"}, "fal ai": {"name": "fal", "docs_url": "https://fal.ai/docs"}, # Cloudflare "cloudflare": {"name": "cloudflare", "docs_url": "https://developers.cloudflare.com"}, "cloudflare waf": { "name": "cloudflare", "docs_url": "https://developers.cloudflare.com/waf", }, # AWS "aws": {"name": "aws", "docs_url": "https://docs.aws.amazon.com"}, "amazon": {"name": "aws", "docs_url": "https://docs.aws.amazon.com"}, # Stripe "stripe": {"name": "stripe", "docs_url": "https://docs.stripe.com/api"}, # Twilio "twilio": {"name": "twilio", "docs_url": "https://www.twilio.com/docs/messaging"}, "twilio sms": {"name": "twilio", "docs_url": "https://www.twilio.com/docs/sms"}, # SendGrid "sendgrid": {"name": "sendgrid", "docs_url": "https://www.twilio.com/docs/sendgrid"}, # Plaid "plaid": {"name": "plaid", "docs_url": "https://plaid.com/docs"}, # Vercel "vercel": {"name": "vercel", "docs_url": "https://vercel.com/docs"}, # Spartan (Angular UI) "spartan": {"name": "spartan", "docs_url": "https://www.spartan.ng/documentation"}, "spartan ui": {"name": "spartan", "docs_url": "https://www.spartan.ng/documentation"}, # Mureka "mureka": {"name": "mureka", "docs_url": "https://docs.mureka.ai"}, # Replicate "replicate": {"name": "replicate", "docs_url": "https://replicate.com/docs"}, # Hugging Face "huggingface": {"name": "huggingface", "docs_url": "https://huggingface.co/docs"}, "hugging face": {"name": "huggingface", "docs_url": "https://huggingface.co/docs"}, "hf": {"name": "huggingface", "docs_url": "https://huggingface.co/docs"}, # Supabase "supabase": {"name": "supabase", "docs_url": "https://supabase.com/docs"}, # Firebase "firebase": {"name": "firebase", "docs_url": "https://firebase.google.com/docs"}, # Vercel "vercel": {"name": "vercel", "docs_url": "https://vercel.com/docs"}, # Netlify "netlify": {"name": "netlify", "docs_url": "https://docs.netlify.com"}, # Discord "discord": {"name": "discord", "docs_url": "https://discord.com/developers/docs"}, "discord api": {"name": "discord", "docs_url": "https://discord.com/developers/docs"}, } def __init__(self): self.http_client = httpx.AsyncClient( timeout=10.0, follow_redirects=True, headers={"User-Agent": "Mozilla/5.0 (compatible; API-Docs-Explorer/1.0)"}, ) def normalize_api_name(self, api_name: str) -> tuple[str, str | None]: """ Normalize API name using aliases. Returns: Tuple of (normalized_name, known_docs_url or None) """ api_lower = api_name.lower().strip() # Check for exact match in aliases if api_lower in self.API_ALIASES: alias = self.API_ALIASES[api_lower] if isinstance(alias, str): return alias, None elif isinstance(alias, dict): return alias.get("name", api_lower), alias.get("docs_url") # Check for partial matches (e.g., "Meta Graph API" contains "meta graph") for key, alias in self.API_ALIASES.items(): if key in api_lower or api_lower in key: if isinstance(alias, str): return alias, None elif isinstance(alias, dict): return alias.get("name", api_lower), alias.get("docs_url") # Clean up common suffixes cleaned = api_lower for suffix in [" api", " sdk", " docs", " documentation"]: if cleaned.endswith(suffix): cleaned = cleaned[: -len(suffix)].strip() # Remove special characters and spaces for URL generation url_safe = re.sub(r"[^a-z0-9]", "", cleaned) return url_safe, None async def find_docs_url(self, api_name: str) -> str | None: """ Dynamically find the official documentation URL for an API. Strategy: 1. Check API aliases for known documentation URLs 2. Try common URL patterns (docs.X.com, X.com/docs, etc.) 3. If patterns fail, return None to trigger search fallback """ # Normalize the API name and check for known URLs normalized_name, known_url = self.normalize_api_name(api_name) # If we have a known URL from aliases, verify it's accessible if known_url: if await self._is_valid_docs_site(known_url): return known_url # Try common patterns with normalized name for pattern in self.DOC_PATTERNS: url = pattern.format(api=normalized_name) if await self._is_valid_docs_site(url): return url # If all patterns fail, return None and let caller search return None def get_search_terms(self, api_name: str) -> list[str]: """ Get alternative search terms for an API. Returns multiple variations to try when searching. """ api_lower = api_name.lower().strip() terms = [api_name] # Original # Add normalized version normalized, _ = self.normalize_api_name(api_name) if normalized != api_lower: terms.append(normalized) # Add common variations if "api" not in api_lower: terms.append(f"{api_name} API") # Check aliases for the canonical name if api_lower in self.API_ALIASES: alias = self.API_ALIASES[api_lower] if isinstance(alias, str): terms.append(alias) elif isinstance(alias, dict) and "name" in alias: terms.append(alias["name"]) return list(dict.fromkeys(terms)) # Deduplicate while preserving order async def _is_valid_docs_site(self, url: str) -> bool: """Check if a URL is a valid documentation site.""" try: response = await self.http_client.head(url, timeout=5.0) # Check for successful response and likely docs content if response.status_code == 200: # Optionally verify it looks like a docs site # by checking content-type or doing a quick GET return True return False except Exception: return False def get_docs_domain(self, docs_url: str) -> str: """Extract the domain from a documentation URL for site-specific search.""" parsed = urlparse(docs_url) return parsed.netloc async def close(self): """Close the HTTP client.""" await self.http_client.aclose() - src/searxng_mcp/api_docs.py:296-530 (helper)Helper class to extract structured information from crawled documentation pages: overview, parameters, code examples, notes, related links, and formats into readable output.
class APIDocsExtractor: """Extract and format API documentation content.""" def extract_overview(self, content: str) -> str: """Extract the overview/description from documentation.""" # Look for common overview sections patterns = [ r"(?:^|\n)#{1,3}\s*(?:Overview|Description|About|Introduction)\s*\n(.*?)(?:\n#{1,3}|\Z)", r"(?:^|\n)(?:Overview|Description):\s*(.*?)(?:\n\n|\Z)", # First substantial paragraph r"(?:^|\n)([A-Z][^.\n]{50,}\.(?:\s+[A-Z][^.\n]+\.){0,3})", ] for pattern in patterns: match = re.search(pattern, content, re.DOTALL | re.MULTILINE) if match: overview = match.group(1).strip() # Clean up and limit length overview = re.sub(r"\s+", " ", overview) if len(overview) > 500: overview = overview[:500] + "..." return overview # Fallback: first paragraph lines = content.strip().split("\n") for line in lines: line = line.strip() if len(line) > 50 and not line.startswith("#"): return line[:500] return "No overview available." def extract_parameters(self, content: str) -> list[dict]: """Extract parameter information from documentation.""" parameters = [] # Pattern for parameter documentation # Matches: "param_name (type, required/optional) - description" param_pattern = r"[\*\-]?\s*`?(\w+)`?\s*\(([^)]+)\)\s*[-–—:]\s*(.+?)(?=\n[\*\-]?\s*`?\w+`?\s*\(|\n\n|\Z)" matches = re.finditer(param_pattern, content, re.DOTALL) for match in matches: name = match.group(1) type_info = match.group(2).strip() description = match.group(3).strip() # Clean up description description = re.sub(r"\s+", " ", description) # Extract if required/optional required = "required" in type_info.lower() parameters.append( { "name": name, "type": type_info, "required": required, "description": description[:300], # Limit length } ) return parameters def extract_examples(self, content: str) -> list[dict]: """Extract code examples from documentation.""" examples = [] # Match code blocks with language specifier code_block_pattern = r"```(\w+)\n(.*?)```" matches = re.finditer(code_block_pattern, content, re.DOTALL) for match in matches: language = match.group(1) code = match.group(2).strip() # Skip very short snippets (likely not examples) if len(code) > 20: examples.append({"language": language, "code": code}) return examples[:10] # Limit to 10 examples def extract_notes(self, content: str) -> list[str]: """Extract important notes, warnings, and tips.""" notes = [] # Look for note/warning/tip sections patterns = [ r"(?:⚠️|⚡|💡|📝|Note|Warning|Important|Tip):\s*(.+?)(?:\n\n|\Z)", r"> (.+?)(?:\n\n|\Z)", # Blockquotes ] for pattern in patterns: matches = re.finditer(pattern, content, re.DOTALL) for match in matches: note = match.group(1).strip() note = re.sub(r"\s+", " ", note) if len(note) > 30 and len(note) < 500: notes.append(note) return notes[:5] # Limit to 5 notes def extract_links(self, content: str, base_url: str) -> list[dict]: """Extract related documentation links.""" links = [] # Match markdown links link_pattern = r"\[([^\]]+)\]\(([^)]+)\)" matches = re.finditer(link_pattern, content) for match in matches: title = match.group(1) url = match.group(2) # Filter for documentation links (not random external links) if any( keyword in title.lower() for keyword in ["api", "docs", "guide", "reference", "tutorial", "see"] ): # Make relative URLs absolute if url.startswith("/"): parsed = urlparse(base_url) url = f"{parsed.scheme}://{parsed.netloc}{url}" links.append({"title": title, "url": url}) # Deduplicate seen_urls = set() unique_links = [] for link in links: if link["url"] not in seen_urls: seen_urls.add(link["url"]) unique_links.append(link) return unique_links[:10] # Limit to 10 links def format_documentation(self, doc: APIDocumentation) -> str: """Format extracted documentation into readable text.""" lines = [ f"API Documentation: {doc.api_name.title()} - {doc.topic}", "═" * 70, "", ] # Overview if doc.overview: lines.extend( [ "📖 Overview:", f" {doc.overview}", "", ] ) # Main documentation URL lines.extend( [ f"📚 Documentation: {doc.docs_url}", "", ] ) # Parameters if doc.parameters: lines.extend( [ "📋 Parameters:", "─" * 70, "", ] ) for param in doc.parameters: req_marker = "required" if param["required"] else "optional" lines.append(f" {param['name']} ({param['type']}, {req_marker})") lines.append(f" {param['description']}") lines.append("") # Code Examples if doc.examples: lines.extend( [ "💡 Code Examples:", "─" * 70, "", ] ) for i, example in enumerate(doc.examples, 1): lines.append(f" Example {i} ({example['language']}):") lines.append(f" ```{example['language']}") # Indent code for code_line in example["code"].split("\n"): lines.append(f" {code_line}") lines.append(" ```") lines.append("") # Important Notes if doc.notes: lines.extend( [ "⚠️ Important Notes:", "─" * 70, "", ] ) for note in doc.notes: lines.append(f" • {note}") lines.append("") # Related Links if doc.related_links: lines.extend( [ "🔗 Related Documentation:", "─" * 70, "", ] ) for link in doc.related_links: lines.append(f" • {link['title']}") lines.append(f" {link['url']}") lines.append("") # Source URLs if doc.source_urls: lines.extend( [ "📄 Sources:", "─" * 70, "", ] ) for url in doc.source_urls: lines.append(f" • {url}") return "\n".join(lines)