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With AI, Everyone is a Dev. EveryDev.ai © 2026
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    3. AEVS
    AEVS icon

    AEVS

    Autonomous Systems

    AEVS is an open-source Python SDK by Fetch.ai that generates tamper-evident, ECDSA-signed receipts for every AI agent tool call, enabling independent audit and verification.

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    At a Glance

    Pricing
    Open Source

    Free to use under Apache 2.0 license. Self-hosted or via AEVS backend with credentials.

    Engagement

    Available On

    Web
    API
    SDK
    CLI

    Resources

    WebsiteDocsGitHubllms.txt

    Topics

    Autonomous SystemsObservability PlatformsAgent Frameworks

    Alternatives

    ManusMoltIDPlurai
    Developer
    Fetch.aiCambridge, United KingdomEst. 2017$68000000 raised

    Listed Jun 2026

    About AEVS

    AEVS (Agent Execution Verification System) is an open-source Python SDK built by Fetch.ai that intercepts AI agent tool calls and produces cryptographically signed, hash-chained receipts for every action. Currently in beta (v0.2.2), it integrates with LangChain, LangGraph, and the Model Context Protocol (MCP) with zero changes to existing agent code.

    What It Is

    AEVS addresses a fundamental gap in AI agent observability: model-generated text describes intent but does not constitute proof of execution. When an agent says "Refund sent," there is no portable, independently verifiable record of which tool ran, with which inputs, or what the API returned. AEVS fills that gap by sitting between the agent and its tools, capturing every invocation and sealing it with an ECDSA P-256 signature backed by a KMS, then linking each receipt to the previous one via a hash chain. The result is a tamper-evident audit trail that auditors can verify using only a reference_id — no access to the codebase or agent logs required.

    How the Receipt Chain Works

    The SDK operates in three stages on every tool call:

    • Catch — AEVS intercepts the invocation and records tool name, inputs, output, timing, and any errors.
    • Sign — Each receipt is ECDSA-signed (P-256) and linked to the previous receipt's hash, so any alteration or skipped entry is detectable.
    • Verify — Anyone with a reference_id can call the public verify API (GET /v1/receipts/verify/<reference_id>) or use the web explorer to confirm the signature independently.

    Receipts are buffered locally in an encrypted SQLite database before being flushed to the AEVS backend over HTTPS via a background thread, making the flow crash-safe.

    Visibility Controls

    AEVS gives developers three receipt visibility modes, set per agent at configuration time:

    • public — Full tool payloads (inputs, outputs, metadata) are visible to anyone with the reference_id or explorer access. Suited for demos and shared audits.
    • private (default) — Full payloads are stored and accessible to the account owner; public verify and explorer show [REDACTED] for inputs and outputs.
    • proof_only — Inputs and outputs are stripped before ingest; only hashes and metadata are kept. Designed for PCI, health, or other regulated data that must not be persisted.

    A separate per-agent dashboard toggle controls whether an agent's receipts appear on the public explorer listing at all, while the verify API remains functional as long as the caller has the reference_id.

    Setup Path

    Installation is a single pip command with optional framework extras:

    • pip install aevs for the base SDK
    • pip install aevs[langchain] for LangChain / LangGraph (requires langchain-core >= 0.2)
    • pip install aevs[mcp] for Model Context Protocol (requires mcp >= 1.20)

    Configuration requires an AEVS_API_KEY and AEVS_AGENT_ID, which can be passed directly or set as environment variables. If credentials are missing, the SDK logs a warning and runs in no-op mode — the agent continues to function normally, receipts simply are not recorded.

    Update: v0.2.2

    The latest release is v0.2.2, published on June 9, 2026. The repository was created in April 2026 and last pushed in June 2026, indicating active early development. The homepage banner explicitly marks AEVS as beta, noting that APIs and the explorer may change. The SDK is licensed under Apache 2.0 and the source is publicly available at fetchai/AEVS-sdk on GitHub.

    AEVS - 1

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    Pricing

    OPEN SOURCE

    Open Source

    Free to use under Apache 2.0 license. Self-hosted or via AEVS backend with credentials.

    • Full SDK source code under Apache 2.0
    • LangChain and MCP integrations
    • Tamper-evident signed receipts
    • Public explorer and verify API
    • Three receipt visibility modes

    Capabilities

    Key Features

    • Tamper-evident signed receipts for every agent tool call
    • ECDSA P-256 signatures backed by KMS
    • Hash-chained receipts for sequential integrity
    • Drop-in SDK with zero changes to existing agent code
    • LangChain and LangGraph integration
    • Model Context Protocol (MCP) integration
    • Independent receipt verification via public API or web explorer
    • Three receipt visibility modes: public, private, proof_only
    • Encrypted local SQLite buffer for crash-safe receipt storage
    • Background thread receipt flushing to AEVS backend
    • Per-agent explorer listing toggle
    • Session and reference ID tracking
    • No-op mode when credentials are absent (agent keeps working)
    • Python 3.10–3.13 support

    Integrations

    LangChain
    LangGraph
    Model Context Protocol (MCP)
    OpenAI (via LangChain)
    ASI:One
    PyPI
    API Available
    View Docs

    Ratings & Reviews

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    Developer

    Fetch.ai

    Fetch.ai builds decentralized AI platforms and services that let anyone deploy AI agents and services at scale. The company develops the uAgents framework, Agentverse, and the AI Engine, enabling autonomous agents to discover, communicate, and transact across a decentralized network. Founded by Humayun Sheikh, Fetch.ai operates the Innovation Lab to support students, entrepreneurs, and businesses building on its agent technology stack. The Innovation Lab runs accelerator programs, internships, hackathons, and ambassador clubs to grow the Fetch.ai developer ecosystem.

    Founded 2017
    Cambridge, United Kingdom
    $68000000 raised
    120 employees

    Used by

    Bosch
    Deutsche Telekom
    Festo
    Catena-X
    Read more about Fetch.ai
    WebsiteGitHubLinkedInX / Twitter
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