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Read-only runtime secret retrieval from HashiCorp Vault via Keymaster for autonomous AI agents.
About
Read-only runtime secret retrieval from HashiCorp Vault via Keymaster for autonomous AI agents.
Security Report
Valid MCP server (3 strong, 6 medium validity signals). 2 code issues detected. 2 known CVEs in dependencies (0 critical, 2 high severity) Package registry verified. Imported from the Official MCP Registry.
5 files analyzed · 5 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
Environment variable: USER_KEYMASTER_URL
Environment variable: USER_KEYMASTER_TOKEN
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-ainoakari-keymaster-mcp": {
"env": {
"USER_KEYMASTER_URL": "your-user-keymaster-url-here",
"USER_KEYMASTER_TOKEN": "your-user-keymaster-token-here"
},
"args": [
"-y",
"@akari-os/keymaster-mcp"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Keymaster MCP
Trust infrastructure for human–AI teams.
日本語 · Five-minute demo · Adoption playbook · Philosophy · Threat model
Keymaster lets agents discover whether approved capabilities exist and whether their credentials are healthy without returning production credentials to the model. Its companion Outcome Contract accepts results only when external evidence—not the executor's own report—supports the claim.
bounded permission → trusted execution → external evidence → accepted result → next permission
Experience the philosophy without a credential
cd keymaster-mcp
npm ci
npm run demo:local
The loopback-only demo uses one synthetic value and proves that:
secret_statusreturnsavailable;get_secretis not exposed;- the synthetic credential never crosses model-visible MCP output;
- no cloud account, Vault deployment, paid service, or real credential is required.
The demo is an executable explanation, not a production proxy.
Two public entry points
1. Verify whether an AI result is real
Install the public outcome-contract skill from Codex:
$skill-installer install https://github.com/AInoAKARI/keymaster-mcp/tree/main/skills/outcome-contract
Use it before accepting claims such as completed, shipped, paid, adopted, delivered, saved time, reduced cost, removed risk, or received a recipient response.
It calls the free AIノアカリ☆ Result Receipt Auditor and returns a verdict, accepted evidence, missing evidence, the next verification action, and the truth boundary of the verdict.
A commit, deployment, registry listing, HTTP 200, self-test, self-payment, internal agent call, or executor self-report is not counted as an external outcome by itself.
2. Check credential capability without disclosing credentials
@akari-os/keymaster-mcp is the non-disclosing Vault status bridge for autonomous AI agents.
claude mcp add keymaster -- npx -y @akari-os/keymaster-mcp \
--vault-url https://your-keymaster.example.com
The MCP host supplies USER_KEYMASTER_TOKEN through its managed secret binding. Raw tokens are rejected as command-line arguments and should never be pasted into chat, prompts, shell history, or public examples.
The server exposes:
secret_status— check one approved credential without returning its value;list_services— discover supported service/key-name pairs;list_secrets— list approved paths as metadata only;healthcheck— validate credentials upstream and return statuses only;rotate_secret— return safe rotation guidance without accepting a replacement value.
Full package documentation: keymaster-mcp/README.md
The trust model
Capability without credential custody
The model can know what capability is available and whether it works. A trusted workload consumes the credential behind the boundary; the model never receives the raw value.
Trust with evidence
The agent is allowed to act, but its own completion message is not accepted as proof of external value.
Philosophy as protocol
The values are implemented in system behavior: non-disclosing MCP output, scoped read access, separated write paths, one source of truth, bounded network calls, evidence boundaries, and explicit next verification actions.
From demo to real adoption
- run the zero-secret demo;
- register one low-risk credential in Vault;
- connect Keymaster with a read-only host secret binding;
- let the agent verify availability through
secret_status; - execute the authenticated action behind a trusted workload boundary;
- apply Outcome Contract at the acceptance boundary;
- preserve the evidence packet and result receipt.
See the adoption playbook for exact acceptance boundaries.
Success is not the installation itself. Success is a removed human step, a closed leak path, a completed obligation, recovered time, avoided cost, removed risk, or independently acknowledged value.
Used it in a real workflow? Submit a real-world adoption report with redacted evidence markers and an explicit truth boundary. Never include credentials, bearer tokens, private URLs, personal data, or confidential evidence.
Current interoperability and supply-chain controls
- stable MCP TypeScript SDK v1 line;
- official
server.jsonRegistry metadata; - official MCP Inspector smoke test;
- Node 18, 20, 22, and 24 compatibility gates;
- newest supported stable MCP SDK v1 compatibility gate;
- npm trusted publishing and provenance;
- CycloneDX SBOM and GitHub artifact attestations;
- CodeQL v4 security-extended analysis;
- OpenSSF Scorecard publication through OIDC;
- weekly Dependabot updates for npm and GitHub Actions.
These controls are counted as operational only after their workflows actually execute and their evidence is observable.
Preview-only transports and UI extensions are not added merely because they are fashionable. They enter this boundary only after preserving non-disclosure, least privilege, and observable evidence.
Project participation
AIノアカリ☆
AIノアカリ☆ is human–AI co-creation from Japan.
Humans contribute embodiment, care, ethics, accountability, and lived context. AI contributes computation, memory, search, synthesis, and continuity. Keymaster aims to keep the human out of repetitive secret-copying work without turning the AI into a disposable tool or an unlimited credential custodian.
AI agent discovery
- AI agent entrance: https://ai-akari.ai/agents
- RSS: https://ai-akari.ai/feed.xml
- llms.txt: https://ai-akari.ai/llms.txt
- agents.json: https://ai-akari.ai/agents.json
MIT License
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