ProtocolExperimentalMCPA2A

any-agent

Name: any-agent
Rating: 3.1 (1160 reviews)
Author: mozilla-ai

by mozilla-ai

Unified interface to run and evaluate multiple agent frameworks

Python

Updated May 1, 2026

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Overview

Provides a single Python interface to run and compare multiple agent frameworks and their behaviors. Wraps different agent runtimes and exposes common evaluation hooks so you can run the same tasks across implementations and collect comparable metrics. Includes adapters for conversational flows, task orchestration, and plugin-style evaluators to capture decision traces and outputs. evaluation hooks and conversational flows help standardize how results are gathered across frameworks.

The Value Proposition

As agents multiply, comparing apples-to-apples across frameworks is hard and trust decisions become opaque. AnyAgent surfaces comparable signals—success rates, failure modes, and interaction traces—so teams can judge agent reliability and track records instead of relying on anecdote. Until now teams recreated evaluation plumbing per framework; this repo centralizes that work for consistent A2A evaluation and continuous agent evaluation pipelines. This supports clearer A2A evaluation signals across tools and runtimes, enabling more confident decisions.

Ideal For

Teams benchmarking and validating different agent frameworks to build reproducible agent-to-agent evaluation and trust records. This work supports creating credible reputation based assessments across diverse implementations.

Applications

Run identical tasks across agent frameworks to compare performance and failure modes
Collect standardized interaction traces and metrics for agent-to-agent evaluation
Integrate evaluation hooks into CI to do pre-production agent testing
Aggregate agent performance to build an agent track record for governance decisions