Ccs Mcp Server

Runtime verification for agent tool calls: Ed25519 signed receipts, fail-closed RCE/SSRF checks.

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Transport
Not stated
Package
Registry id
io.github.DSHCorrectover/ccs-mcp-server

No install snippet on purpose. A working MCP config is a command, its arguments and an environment block — the last two are where API keys live, so this catalogue never stores them and cannot publish them. Follow the link above for the authors' own instructions.

A Model Context Protocol (MCP) server that brings CCS runtime verification to any MCP-compatible client — Claude Desktop, Cursor, Windsurf, and more.

It verifies AI agent tool calls at runtime, blocks unsafe ones by default, issues tamper-evident evidence records for every decision, and verifies that actual tool arguments match the agent's declared intent — catching cross-model parameter drift.

Runtime evidence layer, not a static scanner. Every decision is enforced at call time and produces independently verifiable cryptographic evidence.

⚡ Quick Start — running in 30 seconds

npx -y ccs-mcp-server

Add it to any MCP client — paste this into your mcpServers config in Claude Desktop, Cursor or Cline:

{
  "mcpServers": {
    "ccs-runtime-evidence": {
      "command": "npx",
      "args": ["-y", "ccs-mcp-server"]
    }
  }
}

Or install from the official MCP Registry: search "Correctover" inside your client, or open registry.modelcontextprotocol.io and find io.github.Correctover/ccs.

No API key, no account, no environment variables required — an Ed25519 signing key is generated automatically on first run (set CCS_KEY_DIR, or CCS_PRIVATE_KEY/CCS_PUBLIC_KEY, only if you want to pin a persistent key). Zero dependencies. Pure Node.js stdlib (Node ≥ 18). No install scripts.

Tools

Tool Purpose
verify_tool_call 7-dimension runtime verification (Structure/Schema/Security/Identity/Integrity/Latency/Cost) + semantic attack-chain analysis + math overflow detection. Blocks by default.
issue_evidence Issue a tamper-evident evidence record (content_hash + evidence_hash, chainable). Produced for allowed AND denied calls.
audit_mcp_config Audit MCP configuration JSON for security risks.
verify_intent_binding Verify actual tool arguments match a declared intent — zero tolerance, zero LLM calls. Catches cross-model parameter drift (planner says amount: 100, executor writes amount: 10000 → DENIED).
verify_receipt Offline-verify a CCS Ed25519-signed receipt: checks the signature against the embedded signer public key, reports tampering, and optionally pins an expected signer key or fingerprint.

Intent Binding — Cross-Model Drift Detection

Agent planners (Claude, GPT) declare one thing; executors (Qwen, DeepSeek) sometimes write another. No existing protocol verifies that actual tool call arguments match the agent's declared intent:

  • AP2 signs human authorization — not LLM intent
  • AgentPay does baseline tolerance (1%) — not zero-tolerance equivalence
  • ACS runs policy decisions — not argument-level equivalence
  • VAP (draft-samal-vap-00) explicitly excludes argument semantics from its wire schema

CCS Intent Binding fills this layer. The agent framework declares a structured intent before execution; CCS verifies actual arguments against it in sub-millisecond, zero-LLM time.

Example: amount drift

// Intent declared by planner
{
  "intent_id": "int-001",
  "intent_type": "payment",
  "fields": {
    "amount": { "value": 100, "binding_mode": "exact" },
    "recipient": { "value": "Alice", "binding_mode": "exact" }
  },
  "issued_at": 1755000000000,
  "ttl_ms": 30000
}

// Actual arguments from executor
{ "amount": 10000, "recipient": "Alice" }

// Result: DENIED — intent_arg_mismatch
// field: amount, expected: 100, actual: 10000

Three binding modes

Mode Behavior Example
exact Deep equality with math normalization 100, 100.0, 1e2 all match; 10000 does not
numeric_tolerance Absolute tolerance 100 ± 0.01 matches 100.005
pattern Regex match on string fields ^[A-Z]{3}$ matches "USD"

No intent declared? Falls through to standard 7-dimension verification. Zero breaking changes.

What It Detects

From the project's README.

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