io.github.inkog-io/inkog
NPM · @INKOG-IO/MCP · SCANNED AUG 4
Security co-pilot for AI agents. Scan for vulnerabilities, audit MCP servers, verify governance.
Available components
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. How we score →
Supply Chain Security83
- No malware found by supply-chain analysis.Pass
- CVE check failed: a known medium-severity CVE affects hono 4.12.33, reached via @modelcontextprotocol/sdk > hono. A fixed version is available. View diagnostics → Fail
- No install/post-install scripts declared.Pass
- Only part of the dependency tree could be resolved (98 of 102), so this covers what we could see, not the whole tree. View diagnostics → Partial
Provenance & Transparency45
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (Apache-2.0).Pass
- Actively maintained (last published 80 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability73
- AI-judged instruction clarity (excellent).Pass
- 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. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management30
- Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.
npm · @inkog-io/mcp
claude mcp add inkog-io-inkog -- npx -y @inkog-io/mcp
codex mcp add inkog-io-inkog -- npx -y @inkog-io/mcp
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"inkog-io-inkog": {
"type": "local",
"command": [
"npx",
"-y",
"@inkog-io/mcp"
],
"enabled": true
}
}
} openclaw mcp add inkog-io-inkog --command npx --arg -y --arg @inkog-io/mcp
mcp_servers:
inkog-io-inkog:
command: "npx"
args: ["-y", "@inkog-io/mcp"] {
"mcpServers": {
"inkog-io-inkog": {
"command": "npx",
"args": [
"-y",
"@inkog-io/mcp"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 4 Aug 26 +3
- CVE-2026-69207 affects this package: medium ▼ security
- Known CVEs: partial → fail ▼ security
- Stability: unverified → 0.30 ▲ functional
- 3 Aug 26 +30
- Provenance: unverified → fail ▼ security
- Install scripts: unverified → pass ▲ security
- Known CVEs: unverified → partial ▲ security
- Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window). security
- Maintenance: unverified → pass ▲ functional
- Dependency health: unverified → partial ▲ functional
- License: unverified → pass ▲ functional
- Schema quality: unverified → excellent ▲ functional
- MCP protocol: unverified → pass ▲ functional
- Licence: Apache-2.0 functional
- 2 Aug 26 +10
- 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. security
- Capabilities: pass → unverified ▼ functional
- 1 Aug 26 +5
- Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window). security
- MCP protocol: unverified → pass ▲ functional
- 31 Jul 26 −25
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 30 Jul 26 +20
- Dependency health: partial → unverified ▼ functional
- Tool coverage: unverified → 100 ▲ functional
- 28 Jul 26 −20
- Tool coverage: 100 → unverified ▼ functional
- Dependency health: unverified → partial ▲ functional
- First check of Schema quality: unverified functional
- 27 Jul 26 45
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 4 Aug 2026 · Analysed npm/@inkog-io/[email protected]
Provenance none
Ecosystem: npm · Outcome: none
Vulnerabilities 1 finding
| ID | CVE | Severity | Vector | Fix available |
|---|---|---|---|---|
| GHSA-8j4g-w8fx-2239 | CVE-2026-69207 | medium | CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L | yes |
Dependencies 98 packages
98 packages in the resolved dependency tree · 98 deprecated · 29 stale.
The dependency tree was only partially resolved, so these counts may be incomplete.
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.
inkog_audit_a2a ~134
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.
| Name | Type | Req | Description |
|---|---|---|---|
| check_delegation_chains | boolean | — | Check for infinite delegation loops and unauthorized handoffs |
| path | string | yes | Path to multi-agent system codebase |
| protocol | string | — | Multi-agent protocol hint (optional, will auto-detect if not specified) |
No output schema declared.
No examples provided.
inkog_audit_mcp_server ~97
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.
| Name | Type | Req | Description |
|---|---|---|---|
| repository_url | string | — | Direct GitHub repository URL to audit |
| server_name | string | — | MCP server name from registry (e.g., "github", "slack", "postgres") |
No output schema declared.
No examples provided.
inkog_compliance_report ~134
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.
| Name | Type | Req | Description |
|---|---|---|---|
| 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 | yes | Path to scan for compliance analysis |
No output schema declared.
No examples provided.
inkog_explain_finding ~127
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.
| Name | Type | Req | Description |
|---|---|---|---|
| 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. |
No output schema declared.
No examples provided.
inkog_generate_mlbom ~113
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.
| Name | Type | Req | Description |
|---|---|---|---|
| format | string | — | Output format: cyclonedx (recommended), spdx, or json |
| include_vulnerabilities | boolean | — | Include known vulnerabilities for detected components |
| path | string | yes | Path to agent codebase to analyze |
No output schema declared.
No examples provided.
inkog_scan ~217
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.
| Name | Type | Req | Description |
|---|---|---|---|
| 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 | yes | 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) |
No output schema declared.
No examples provided.
inkog_verify_governance ~99
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.
| Name | Type | Req | Description |
|---|---|---|---|
| path | string | yes | Path to directory containing AGENTS.md and agent code |
No output schema declared.
No examples provided.