correctover-mcp-server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@correctover-mcp-serverRun CCS verification on agent-123's tool call"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
CCS Runtime Evidence MCP Server
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-serverAdd 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.
Related MCP server: signet-eval
Tools
Tool | Purpose |
| 7-dimension runtime verification (Structure/Schema/Security/Identity/Integrity/Latency/Cost) + semantic attack-chain analysis + math overflow detection. Blocks by default. |
| Issue a tamper-evident evidence record ( |
| Audit MCP configuration JSON for security risks. |
| Verify actual tool arguments match a declared intent — zero tolerance, zero LLM calls. Catches cross-model parameter drift (planner says |
| 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: 10000Three binding modes
Mode | Behavior | Example |
| Deep equality with math normalization |
|
| Absolute tolerance |
|
| Regex match on string fields |
|
No intent declared? Falls through to standard 7-dimension verification. Zero breaking changes.
What It Detects
Command injection: shell metacharacters,
curl|sh,rm -rf,eval()Path traversal:
../,/etc/passwd,/proc/self/SSRF:
169.254.169.254(cloud metadata), localhost, private ranges — across any toolCross-tool attack chains: read sensitive file → network exfil =
exfil_chainEnvironment variable exfiltration: API keys, secrets, credentials
Obfuscation: hex encoding, base64, privilege escalation signals
Math safety: integer overflow (>2^53-1), NaN/Infinity
MCP config risks: plain HTTP, weak secrets,
--insecure, TLS disabled
Evidence Chain
Every decision produces evidence with dual hashes (content_hash + evidence_hash) and chain linkage (parent_evidence_hash). Any third party can independently verify that evidence has not been tampered with — without trusting the operator.
evidence 1: allowed (fs.read_file) parent: null
evidence 2: denied (shell.exec curl|sh) parent: ev1
evidence 3: denied (http.fetch SSRF) parent: ev2
evidence 4: denied (fs + curl exfil) parent: ev3Receipts are Ed25519-signed and JSON-based: verify them offline with the built-in verify_receipt tool, or independently with any Ed25519 library. Cross-tool receipt verification (same crypto, chain linkage, field mapping) is designed to work without this package installed.
The 7 CCS Dimensions
Structure — valid tool name, argument format, nesting depth, payload size
Schema — type, required fields, enums, ranges, string lengths
Security — injection, traversal, SSRF, env exfiltration, obfuscation + semantic attack chains
Identity — caller agent ID verification
Integrity — request hash validation
Latency — execution time budget
Cost — cost budget
Protocol Context
IETF: draft-correctover-ccs — an individual Internet-Draft; not an RFC or IETF endorsement, and the Datatracker page is authoritative for revision and status
Complements: VAP draft-samal-vap-00 (scope/budget/purpose), Microsoft ACS (policy decisions), AP2 (human authorization)
Does not replace: authentication, payment networks, policy engines
Links
IETF Draft: https://datatracker.ietf.org/doc/draft-correctover-ccs/
PyPI (full verifier): https://pypi.org/project/ccs-verifier/
License
Elastic License 2.0 (ELv2). See LICENSE.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
No tool schema history has been recorded yet.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Deterministic runtime safety for AI agents: scan PII, gate tool actions, verify LLM output.
Runtime permission, approval, and audit layer for AI agent tool execution.
Zero-trust gateway for AI agents: score tool calls, verify agent cards, enforce policy, audit.
Pre-execution governance for AI agents. Deterministic PASS/FAIL/REVIEW verdicts, replayable proof.
Related MCP Servers
- AlicenseCqualityBmaintenanceA fail-closed preflight, approval, evidence, and verification runtime for agents, preventing unsupported output from being treated as verified completion.3MIT
- AlicenseNot gradedqualityBmaintenanceDeterministic policy enforcement for AI agent tool calls. It evaluates every tool call against user-defined rules before execution, with no LLM in the authorization path.3MIT
- FlicenseNot gradedqualityBmaintenanceProvides a secure MCP boundary for AI agents, intercepting and validating tool calls, redacting secrets, and requiring human approval for sensitive actions with a tamper-evident audit trail.-
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to enforce spec-driven development and verify code before it is marked done, using six tools that catch invented APIs, scan for hallucinated content, check plugin conformance, sandbox-run tests, validate schemas, and record audit evidence.5907PolyForm Noncommercial 1.0.0
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/DSHCorrectover/ccs-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server