Python SDK v1 · Coming Soon

Behavioral Attestation
& Intent Detection

Intent detection that flags agent tool calls drifting from user request.
Bidirectional cryptographic proofs over every MCP interaction.
Anti-hallucination circuit breakers and reputation built on verified actions.

Bidirectional Proof
Anti-Hallucination
Agent Reputation
On-Chain Ready
zeroproof / proof_stream
12:04:31.0020x7f3aweb_searchverified
12:04:31.1180x9d2cfile_writeverified
12:04:31.2040x4e1bexec_pythonverified
12:04:31.3910x2a8fdb_queryrejected
12:04:31.4770x6c5esend_emailpending
12:04:31.5830x1d9afetch_urlverified
Products

Two ways to build with ZeroProof

01 / Behavioral Attestation

Prove that an AI took a tool call

A public attestation service for MCP tool interactions. Generate tamper-proof receipts for every tool call your agent makes. Auditable by anyone, anchored on-chain.

# example receipt
tool: web_search
agent: gpt-agent-7f3a
proof: sha256:a1b2c3…
chain: base:0x9d2c…
02 / Intent Detection

Prove the LLM is doing what you asked

Fine-tuned models that compare agent tool calls against the original user intent. Catch hallucinated actions, scope drift, and unauthorized operations before they execute.

Intent alignment
0.97
Scope adherence
0.94
Hallucination risk
0.03
View on HuggingFaceUpcoming
Protocol

How ZeroProof works

01

Agent issues a tool call

Your MCP-connected agent sends a tool request. ZeroProof intercepts it at the protocol layer.

02

Intent model runs

A fine-tuned model checks whether the tool call matches the original user request.

03

Proof is generated

A bidirectional cryptographic receipt is issued, signed by both the agent and the tool server.

04

Reputation is updated

The verified action is anchored on-chain, building a tamper-proof agent reputation score.

From “trust me” to “verify it yourself”

ZeroProof is in early access. Get notified when the Python SDK ships and be first to make your agents verifiable.