Repository intelligence

Agenta-AI/agenta

An open-source workspace and collaboration platform where teams can build, test, version-control, and deploy specialized AI agents that run interactively or automatically in the background.

CLOUDM0N decision

Trust FAIL · 10/100

Good fit if

Teams seeking a shared workspace to collaborate on documents, research, or wikis alongside specialized AI agents.

Watch out for

You need to build deterministic, static, step-by-step API integration chains that require zero autonomous planning or agentic reasoning.

Practical intelligence

What matters before you adopt it

Decision first · detail on demand

Problem it solves

The lack of centralized versioning, collaborative workspaces, and structured debugging workflows for AI agents, as well as the high metered cost of running development agents directly through commercial APIs.

Best for

Teams seeking a shared workspace to collaborate on documents, research, or wikis alongside specialized AI agents.

Developers wanting to self-host and run AI agents locally using their existing personal Claude or ChatGPT subscriptions to avoid metered developer API bills.

Organizations looking to automate complex processes that require reasoning, adaptive planning, and human-in-the-loop validation rather than simple, predictable sequential workflows.

Main trade-offs

You need to build deterministic, static, step-by-step API integration chains that require zero autonomous planning or agentic reasoning.

Why it stands out

Highly permissive MIT open-source license.

Built around open standards, enabling teams to import custom skills, AGENTS.md definitions, and ecosystem MCP servers.

Maintains deep trace history and version-control mapping of all configurations to diagnose, compare, and fix agent failures.

Trust & CVEs

Security evidence without the noise

Trust remains a decision signal; CVEs and scanner evidence explain what is driving the risk.

Security findings

CLOUDM0N scanner findings

Critical

High

Medium

Low

View trust evidence & security findings▼

Why this score

No trust rationale was stored for this scan.

CLOUDM0N findings

CRITICAL

Private-key material appears to be committed in executable/config scope. 1 sample match(es) found.

HIGH

Container configuration requests host-level control or isolation bypass. 5 sample match(es) found.

MEDIUM

Dynamic code execution pattern detected. 5 sample match(es) found.

MEDIUM

The project can spawn operating-system processes; review command construction and input handling. 5 sample match(es) found.

Architecture from code6 modules · 0 edges▼

Structural evidence

Modules and dependency edges extracted from repository code. This is code evidence, not README inference.

Code files

2443

Modules

Dependency edges

Core modules

antd-inventory

2 files

api

API layer

1448 files

benchmarks

3 files

clients

950 files

Dependency flow

No dependency edges were extracted.

Detected languages

Python · Shell · TypeScript · JavaScript · SQL

Detected frameworks

FastAPI · Requests

Architecture evidence details

flowchart TD
    %% repo — high-level architecture (DRAFT, refine me)
    n0["antd-inventory · 2 files"]
    n1["api · API layer · 1448 files"]
    n2["benchmarks · 3 files"]
    n3["clients · 950 files"]
    n4["docs · documentation · 40 files"]
    class n1 api
    class n4 docs
    classDef api fill:#af7aa1,color:#ffffff,stroke:#8a5f7f
    classDef docs fill:#9d7660,color:#ffffff,stroke:#7c5d4c

Evidence, security & integrations▼

Integrations

Claude CodePiCodexOpenAIAnthropicOpenRouterMistral AICohere

Security notes

• Enables role-based access control (RBAC) to securely manage team permissions on the open-source version.

• Features explicit tool permissions that allow administrators to choose which actions background agents can execute autonomously, which are blocked, and which require manual human approval.

Still unknown

• The README does not provide concrete system resource requirements, minimum RAM, or database configuration prerequisites for hosting the server.

• The exact script commands to execute local self-hosting setup are omitted from the text, redirecting instead to an external quick-start documentation URL.

• The README does not state any operational trade-offs, constraints, or limitations of self-hosting the platform.

Adoption guidance▼

Adopt if

+ You are deploying AI agents (such as Claude Code or Codex) and require deep execution tracing, configuration version control, and granular team permissions.

+ You want to utilize personal LLM subscriptions to run your team's background automations locally to manage API costs.

Avoid if

– You need to build deterministic, static, step-by-step API integration chains that require zero autonomous planning or agentic reasoning.

– You require immediate, native production support for E2B sandboxes or mobile client applications, which are currently marked as planned roadmap items.

How it works & getting started▼

How it works

1.The user signs up for Agenta Cloud or boots up a self-hosted local instance.

2.The user defines their agent's traits, skills, and tools via conversational chat or by using standard AGENTS.md templates.

3.The user connects model harnesses, local sandbox runtimes, and application integrations.

4.The user sets up scheduling parameters, trigger events, and specific human-in-the-loop approval rules.

5.The agent executes tasks, while the server logs comprehensive traces, calculates token costs, and handles background loops.

Getting started

→ Sign up for an account directly on Agenta Cloud for the fastest setup.

→ To self-host, paste the quicksetup command described in the self-hosting documentation into your target workspace or agent configuration.

→ Reference the official quick-start self-hosting documentation at agenta.ai/docs/self-host/quick-start for full manual installations.

Agent handoff

Use with any agent

JSON API

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