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Vaara

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Runtime governance proxy for MCP servers. Risk scoring, hash-chained audit, per-tenant policy.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "vaara": {
      "command": "npx",
      "args": [
        "-y",
        "vaara"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

Vaara

PyPI License CI OpenSSF Scorecard Vaara Conformance: 46 suites, 0 failing DOI 10.5281/zenodo.22027975 OpenSSF Best Practices Hugging Face Space

Downloads

Accountable Autonomy.

A verifiable receipt for every autonomous action, checkable by anyone.

Your AI agent transferred the funds, wrote the file, called the tool. Later, someone who does not trust you asks you to prove exactly what it did and why: a regulator, an auditor, a customer after an incident. Your own logs will not settle it, because you could have edited them.

Vaara for macOS launch demo

Quick start

Terminal
pip install vaara                            # Python: CLI, MCP proxy, server
brew tap vaaraio/tap && brew install vaara   # macOS: CLI + menu-bar app (built from source)
npm install @vaara/client                    # TypeScript client for the HTTP API
server.ts
import vaara

@vaara.govern
def transfer_funds(to: str, amount: float) -> str:
    ...

That is the whole thing. Every call to a governed function is risk-scored and decided against your policy before the body runs. An allowed call runs, and the decision, the call, and the outcome land in a hash-chained, tamper-evident record anyone can verify offline. Sign it at export (vaara trail export) for third-party proof. Records persist to ~/.vaara/trail/audit.db by default, so evidence survives restarts. Python 3.10+, zero runtime dependencies.

Both deny and escalate raise vaara.Blocked, since an escalation means a human has not answered yet. Run the example above on a fresh install and it will raise: with no outcome history the scorer's confidence interval is wide, and a tx.transfer escalates on the interval's upper bound even though its point estimate sits under the allow threshold. That is the intended direction to fail, and it settles. Feeding real outcomes back through report_outcome narrows the interval, and the same call starts allowing after a few dozen clean results. To watch decisions without acting on them while that happens, start with @vaara.govern(shadow=True).

Check a receipt with nothing installed

vaara.io/verify.html is the Vaara Resin. One HTML file, no build step and no dependencies. Paste in a receipt and it recomputes the DSSE pre-authentication encoding, takes its digest, and checks the Ed25519 signature with WebCrypto. The receipt never leaves the tab, nothing uploads, and the page works with the network off, so verification is not a service and Vaara is not a party to it. Save the file and it keeps working.

It also states what a passing check does not establish: that the key belongs to the party you expect, that the signed statement is true, that decided_at means anything without an external time authority, or that one receipt is a whole history.

The explorer on the same page reads the public transparency log straight from your browser. Look a trail head up by digest, or paste a public key to see everything published under it. No account and no sign-in, because the key is the identity. Publishing to that log is opt-in and off by default (vaara trail publish-head), so an absence there means nothing was published rather than nothing happened.

See who else has checked it

vaara.io/conformance.html is the results page. It carries every suite and its verdict, and every party other than the maintainer who ran the checkers and reported what they found in public. Rows are chained, each holding the digest of the row before it, so removing or reordering one breaks every digest after it and the break is visible to anyone. The maintainer cannot take a row down either. A run that disagrees with ours is a row too, with the reason stated, and there is no blacklist.

The aggregate runner grades every suite at once, and grades another implementation's vectors the same way:

bash
python scripts/conformance_runner.py                                 # grade the reference corpus
python scripts/conformance_runner.py --vectors-dir ./your_vectors    # grade your own

It prints a prefilled link at the end of every run, so asking for a row takes one click. The named, versioned rule set, what a pass does and does not establish, and the full suite list are in docs/conformance-profile.md.

Prefer the explicit pipeline?

The decorator drives the same engine you can call directly when you want the decision object in hand.

server.ts
from vaara.pipeline import InterceptionPipeline

pipeline = InterceptionPipeline()
result = pipeline.intercept(
    agent_id="agent-007",
    tool_name="fs.write_file",
    parameters={"path": "/etc/service.yaml", "content": "..."},
    agent_confidence=0.8,
)
if result.allowed:
    pipeline.report_outcome(result.action_id, outcome_severity=0.0)
else:
    print(result.reason)

Every call gets a risk score and an allow / block / escalate decision against your policy, then the call, the decision, and the real outcome are written to the audit trail. report_outcome closes the loop: the scorer reweights based on which signals actually predicted the outcome. Releases ship SLSA Build Level 3 provenance, verifiable with slsa-verifier verify-artifact. Optional ML classifier: pip install 'vaara[ml]'.

Verify it without trusting the producer

Writing a trail is the easy half. The half that matters is letting someone who does not trust you check it, with no key, no access, and none of your code. Every Vaara record is content-addressed and fail-closed on authenticity, and ships with public conformance vectors plus a standalone checker that imports no Vaara code, so an independent party reproduces every verdict offline.

bash
vaara verify-bundle evidence-bundle.json

ok only when a signature is actually established, not merely present in a log. The same property drives the standards work behind the Vaara Receipt Internet-Draft: evidence that holds up for someone who runs none of your software. The full verifier set, the trust model for each verb, and where trust comes from in each case are in docs/verifying-evidence.md.

To check that claim yourself, without installing Vaara, run the standalone checker against the published vectors. Its only dependencies are cryptography and rfc8785:

bash
git clone https://github.com/vaaraio/vaara
cd vaara
pip install cryptography rfc8785        # the checker's only dependencies
python tests/vectors/external_evidence_v0/_check_independent.py

It re-derives every verdict from the receipt bytes and the public key alone. The output shows the property the trail is built for: a receipt dropped from inside a declared boundary is a provable gap from the held set, with no issuer access and no external witness.

For the whole loop in one runnable file, produce a signed record, verify it yourself, then watch a single forged byte get caught, see examples/prove-it-yourself/. The logs-versus-evidence argument behind it is in docs/logs-vs-evidence.md.

What the evidence looks like

vaara compliance report --format json against a real trail produces an article-level evidence record an auditor reads directly. Articles with no recorded events return evidence_insufficient, not a rubber stamp.

config.json
{
  "system_name": "Acme HR Assistant",
  "overall_status": "evidence_insufficient",
  "trail_integrity": {"size": 105, "chain_intact": true},
  "articles": [
    {"article": "Article 12(1)", "title": "Record-Keeping (Logging)",
     "status": "evidence_sufficient", "strength": "strong", "evidence_count": 105},
    {"article": "Article 15(1)", "title": "Accuracy, Robustness and Cybersecurity",
     "status": "evidence_insufficient", "strength": "absent", "evidence_count": 0}
  ]
}

Read the full README β†’View source on GitHub β†’

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Frequently Asked Questions about Vaara

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "vaara": { "command": "npx", "args": ["-y", "Vaara"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
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27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
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Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

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