# io.github.inkog-io/inkog (npm · @inkog-io/mcp)

Security co-pilot for AI agents. Scan for vulnerabilities, audit MCP servers, verify governance.

- Trust score: 68/100 (medium)
- Change this week: +43
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-04

## Components

- npm · `@inkog-io/mcp`: 68/100 (this document), [markdown](https://verifymcp.io/servers/inkog-io-inkog/inkog-io-mcp.md), [page](https://verifymcp.io/servers/inkog-io-inkog/inkog-io-mcp)

## Channel facts

- Registry: `npm`
- Package: `@inkog-io/mcp`
- Version: `1.0.20`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-04.

- **Supply Chain Security**: 83/100
  - No malware found by supply-chain analysis.
  - CVE check failed: a known medium-severity CVE affects hono 4.12.33, reached via @modelcontextprotocol/sdk > hono. A fixed version is available.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (98 of 102), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (Apache-2.0).
  - Actively maintained (last published 80 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 73/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 921 tokens (~131/item across 7 items; 7 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 30/100
  - Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add inkog-io-inkog -- npx -y @inkog-io/mcp
```

### Codex

```bash
codex mcp add inkog-io-inkog -- npx -y @inkog-io/mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "inkog-io-inkog": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@inkog-io/mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add inkog-io-inkog --command npx --arg -y --arg @inkog-io/mcp
```

### Hermes

```yaml
mcp_servers:
  inkog-io-inkog:
    command: "npx"
    args: ["-y", "@inkog-io/mcp"]
```

### Other

```json
{
  "mcpServers": {
    "inkog-io-inkog": {
      "command": "npx",
      "args": [
        "-y",
        "@inkog-io/mcp"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-04 (score 68, +3)

- [security regression] CVE-2026-69207 affects this package: medium
- [security regression] Known CVEs: partial → fail
- [functional improvement] Stability: unverified → 0.30

### 2026-08-03 (score 65, +30)

- [security regression] Provenance: unverified → fail
- [security improvement] Install scripts: unverified → pass
- [security improvement] Known CVEs: unverified → partial
- [security] Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window).
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] License: unverified → pass
- [functional improvement] Schema quality: unverified → excellent
- [functional improvement] MCP protocol: unverified → pass
- [functional] Licence: Apache-2.0

### 2026-08-02 (score 35, +10)

- [security improvement] Malware scan: unverified → pass
- [security] Stability: Stability not yet verified: we do not have a sandbox capture of the MCP schema this version of the package serves yet.
- [functional regression] Capabilities: pass → unverified

### 2026-08-01 (score 25, +5)

- [security] Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window).
- [functional improvement] MCP protocol: unverified → pass

### 2026-07-31 (score 20, −25)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 45, +20)

- [functional regression] Dependency health: partial → unverified
- [functional improvement] Tool coverage: unverified → 100

### 2026-07-28 (score 25, −20)

- [functional regression] Tool coverage: 100 → unverified
- [functional improvement] Dependency health: unverified → partial
- [functional] First check of Schema quality: unverified

### 2026-07-27 (score 45)

First indexed and scored.

## MCP tools (7)

### `inkog_scan` (~217 tokens)

Security co-pilot for AI agent development. Scans for prompt injection, infinite loops, token bombing, SQL injection via LLM, and missing guardrails. Supports LangChain, CrewAI, LangGraph, AutoGen, n8n, and 20+ agent frameworks. Use this whenever building, reviewing, or deploying AI agents to catch security issues before they reach production.

Input parameters:

- `agent_name` (string): Agent name for dashboard identification (auto-detected from path if not provided)
- `filter` (string): File filtering: auto (detect agent repos, adapt filtering), agent-only (aggressive filtering), all (no filtering)
- `output` (string): Output format: summary (default), detailed (full findings), sarif (for CI/CD)
- `path` (string, required): File or directory path to scan
- `policy` (string): Security policy: low-noise (proven vulnerabilities only), balanced (default), comprehensive (all findings), governance (Article 14 focused), eu-ai-act (compliance mode)

### `inkog_verify_governance` (~99 tokens)

Validate that AGENTS.md declarations match actual code behavior. Detects governance mismatches like 'read-only declared but code writes data' or 'human approval required but no approval gates in code'. Essential for EU AI Act Article 14 compliance. Use this whenever an AI agent project has an AGENTS.md file, or to verify governance compliance before deployment.

Input parameters:

- `path` (string, required): Path to directory containing AGENTS.md and agent code

### `inkog_compliance_report` (~134 tokens)

Generate a compliance report for EU AI Act, NIST AI RMF, ISO 42001, or OWASP LLM Top 10. Analyzes agent code and maps findings to regulatory requirements. Use this when preparing AI agents for regulatory compliance or audit.

Input parameters:

- `format` (string): Output format: markdown (default), json, or pdf
- `framework` (string): Compliance framework: eu-ai-act (default), nist-ai-rmf, iso-42001, owasp-llm-top-10, or all
- `path` (string, required): Path to scan for compliance analysis

### `inkog_explain_finding` (~127 tokens)

Get detailed explanation and remediation guidance for a security finding or pattern. Includes what the issue is, why it's dangerous, step-by-step fixes, and code examples. Use this after scanning to understand how to fix security findings.

Input parameters:

- `finding_id` (string): Finding ID from scan results (e.g., "f8a3b2c1")
- `pattern` (string): Pattern name: prompt-injection, infinite-loop, sql-injection-llm, token-bombing, hardcoded-credentials, missing-rate-limits, recursive-delegation, etc.

### `inkog_audit_mcp_server` (~97 tokens)

Security audit any MCP server from the registry or GitHub. Analyzes tool permissions, data flow risks, input validation, and potential vulnerabilities. Use this before installing any new MCP server to verify it is safe.

Input parameters:

- `repository_url` (string): Direct GitHub repository URL to audit
- `server_name` (string): MCP server name from registry (e.g., "github", "slack", "postgres")

### `inkog_generate_mlbom` (~113 tokens)

Generate a Machine Learning Bill of Materials (MLBOM) for AI agents. Lists all models, tools, data sources, frameworks, and dependencies. Supports CycloneDX and SPDX formats. Use this when documenting AI agent dependencies for supply chain compliance.

Input parameters:

- `format` (string): Output format: cyclonedx (recommended), spdx, or json
- `include_vulnerabilities` (boolean): Include known vulnerabilities for detected components
- `path` (string, required): Path to agent codebase to analyze

### `inkog_audit_a2a` (~134 tokens)

Audit Agent-to-Agent (A2A) communications in multi-agent systems. Detects infinite delegation loops, privilege escalation, data leakage between agents, and unauthorized handoffs. Supports Google A2A protocol, CrewAI, LangGraph, and AutoGen. Use this when building or reviewing multi-agent systems to detect delegation vulnerabilities.

Input parameters:

- `check_delegation_chains` (boolean): Check for infinite delegation loops and unauthorized handoffs
- `path` (string, required): Path to multi-agent system codebase
- `protocol` (string): Multi-agent protocol hint (optional, will auto-detect if not specified)

## Diagnostics

Captured diagnostic sections: Provenance, Vulnerabilities, Dependencies. The full working is on the page: https://verifymcp.io/servers/inkog-io-inkog/inkog-io-mcp#diagnostics

## Score history

- 2026-08-04: 68
- 2026-08-03: 65
- 2026-08-02: 35
- 2026-08-01: 25
- 2026-07-31: 20
- 2026-07-30: 45
- 2026-07-28: 25
- 2026-07-27: 45

## Links

- npm package: https://www.npmjs.com/package/@inkog-io/mcp
- Socket report: https://socket.dev/npm/package/@inkog-io/mcp
- Repository: https://github.com/inkog-io/inkog-mcp
- Changelog RSS feed: https://verifymcp.io/servers/inkog-io-inkog/inkog-io-mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/inkog-io-inkog/inkog-io-mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/inkog-io-inkog/inkog-io-mcp