CadenceMCP ⓘ SEP-1649 Card
📚 Explore SDK Directory 📊 ROI Calculator ⚡ Get API Key & Pricing →

Real-Time Code & API Guard for AI Agents

AI models can rely on outdated training data — CadenceMCP feeds your agent live API signatures so code works on the first try, saving tokens and cutting dev costs.

⚡ The 10-Second Pitch

Stop Paying Twice To Get Working AI Code

Why spend tokens on an AI module when one deprecated API call breaks the whole output? It's like buying spoiled fruit, then paying again for fresh fruit — double the cost.

Step 1 • The Prompt

🛒 Tokens Spent to Travel

You spend tokens traveling to the store — sending your prompt and codebase context to your AI agent.

Step 2 • The Response

🛍️ Grocer Hands You Fruit

The grocer wraps your fruit and hands it over — the AI generates a full code payload and delivers it.

Step 3 • The Crash

🍏 Spoiled Fruit at Home

You come home only to find a piece of fruit is spoiled — the whole generated file fails because 1 deprecated method crashed at runtime.

Step 4 • The Solution

✨ CadenceMCP Guardrail

CadenceMCP equips your AI via MCP to verify API signatures before generating code. Zero broken responses. Zero wasted tokens.

💡 The Takeaway: Don't burn tokens re-prompting AI to fix code it just broke. MCP gives your agent live signature context to get the whole response right on the first try.

Calculate ROI & Savings ↓

ROI Impact Matrix & Interactive Savings Calculator

Supports teams from 1 solo developer up to 500+ engineers

⚡ Live Financial Model
$298,350
Total Annual Enterprise Savings
3,375
Dev Hours Saved / Year
50 Developers
25 Queries / Day
$0.04 / Retry
$85 / Hour
Parameter Input Example Input Calculated Enterprise Impact
Engineering Team Size 50 Developers 3,375 Dev Hours Saved / Year
AI Coding Queries / Dev / Day 25 Queries / Day $11,250 LLM Token Waste Avoided / Year
Token Waste per Failed Retry $0.04 / Retry $298,350 Total Annual Enterprise Savings
Developer Hourly Rate $85 / Hour Payback Period: < 2 Days ($79/mo tier)
🚀 Get Instant Access via Stripe ($79/mo) →

3 Core Differentiators Giving CadenceMCP the Edge

Architectural advantages that make CadenceMCP faster, lower-cost, and more accurate than competitors.

01

CadenceMCP Deterministic AST-Diff™ Architecture

Competitors (Cursor @docs, Context7): Use vector embeddings to match user queries with scraped documentation chunks. Vector search retrieves similar-sounding old docs, leading LLMs to still generate deprecated code.
CadenceMCP Moat: Operates via CadenceMCP's proprietary Deterministic AST-Diff™ Architecture (built on Tree-sitter). When querying a method in openai-python v1.20, returns the exact structural AST diff and signature patch from v0.28, eliminating hallucinated syntax entirely.
02

Zero-LLM Instant Context Path (<25ms Speed)

Competitors (Greptile, CodeRabbit): Execute live LLM inference calls or heavy multi-step agentic loops to process context queries. This costs pennies per query and takes 2 to 10 seconds.
CadenceMCP Moat: Eliminates live LLM calls during context retrieval. Serves pre-parsed, cached JSON/AST snapshots directly from DuckDB/SQLite in <25ms at <$0.00004 per request, enabling the aggressive $79 for 2,000,000 requests tier.
03

Epoch-Partitioned Merkle Integrity Trees & Upcasting

Competitors: Only know about "the latest docs" or manually scraped versions. If an enterprise is locked to an older SDK version (e.g., Pydantic v1 or React 18), standard doc tools serve incorrect v2/v19 guidance.
CadenceMCP Moat: Tracks historical Epoch-Partitioned Merkle Integrity Trees and features a dynamic Schema Upcaster Layer. Serves the exact SDK version syntax requested by the client's X-Schema-Version or checkpoint tag.

⚡ Test Real-Time Deprecation Lookup

Test any third-party SDK symbol below to see how CadenceMCP returns instant, deterministic AST diff patches to AI agents:

Universal Protocol Support: FastMCP, REST, & llms.txt

Model Context Protocol

⚡ FastMCP Protocol Stream

Native Model Context Protocol (MCP) streamable HTTP endpoint built for Cursor, Claude Code, Windsurf, Gemini, and Cline agents.

https://api.cadencemcp.com/v1/mcp
REST / OpenAPI Specs

🌐 REST & OpenAPI Fallback

Auto-generated OpenAPI spec endpoint for OpenAI Custom GPTs, LangChain, LlamaIndex, and traditional webhooks without MCP dependencies.

Inspect /openapi.json Spec →
LLM Search Standard

📄 llms.txt Standard

Clean markdown answer engine documentation optimized for Perplexity, ChatGPT Search, and Claude Web Search crawlers.

View /llms.txt Standard →

Visual Proof: Broken Code vs. CadenceMCP Guard

❌ Without CadenceMCP (Error)

AI generates outdated code based on static training cutoff data:

// OUTDATED SYNTAX (Fails at runtime)
import openai

res = openai.ChatCompletion.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "hi"}]
)

Result: AttributeError: module 'openai' has no attribute 'ChatCompletion'

✅ With CadenceMCP (Correct)

AI agent queries CadenceMCP and receives modern AST diff patch:

// MODERN SYNTAX (Works on first try)
from openai import OpenAI

client = OpenAI()
res = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "hi"}]
)

Result: 200 OK — Clean execution on first try!

1-Click Agent Setup Guides (Supported AI Agents & Frameworks)

Copy-paste ready rules & tool definitions with direct links to official agent platforms.

Add this block to your project's .cursorrules file:

Official Cursor Site ↗
# Cursor Rules: CadenceMCP Integration Guard
Before generating code for third-party SDKs (Stripe, OpenAI, Supabase, Tokio, PyTorch, etc.), query CadenceMCP tool `check_signature_deprecation`:
FastMCP Endpoint: https://api.cadencemcp.com/v1/mcp
Deprecation Check API: https://api.cadencemcp.com/v1/check-signature?library={LIBRARY}&symbol={SYMBOL}
Parameters: library (e.g. "openai-python"), symbol (e.g. "openai.ChatCompletion.create")
Authorization: Bearer unkey_live_your_api_key_here