- Teams operating LLM and agent applications
- Builders comparing self-hostable evaluation and observability platforms
- AI teams that need simulations, datasets, and guardrails together
Apache-2.0 ยท Tools
Future AGI
Open-source platform for evaluating, observing, and improving LLM and AI agent applications.
1.1K stars 0.2K forks Apache-2.0 license 2026-06-11 verified
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# Future AGI$
pip install future-agi$
npx future-agi --help Open sourceSelf-hosted
Overview
What is Future AGI?
Future AGI is an open-source platform for evaluating, observing, and improving LLM and AI agent applications. It covers tracing, evals, simulations, datasets, gateway workflows, guardrails, and self-hostable deployment.
Evaluation and observability together
Future AGI combines tracing, evals, datasets, simulations, gateway, and guardrails.
Production agent quality depends on multiple feedback loops, not just a dashboard.Self-hostable platform
The project describes itself as self-hostable.
Teams with sensitive agent data often need control over telemetry and evaluation datasets.Agent application focus
Future AGI is explicitly aimed at LLM and AI agent applications.
Agent systems need tool, trace, and workflow-level evaluation beyond plain chat completion metrics. Use cases
What teams use it for
Ecosystem
Tags & capabilities
Comparison
How it stacks up
When to choose Future AGI
Compare it with nearby tools by looking at hosting model, integration surface, license, and whether the official docs show the workflow you need.
FAQ
Questions
Is Future AGI open source?
Yes. The GitHub repository is listed under the Apache-2.0 license.
Who should evaluate Future AGI?
Teams shipping production LLM or agent applications should evaluate it as an evaluation and observability layer.
Decision brief
JSON
Should you use Future AGI?
- Small prototypes that only need a few manual test prompts
- Teams looking for a low-level agent framework rather than an operations platform
- Verified 2026-06-11
- License: Apache-2.0
- Repo: future-agi/future-agi
- Open-source signal
Deployment
self hosted, cloud
Permission surface
Low explicit permission surface in metadata
Decision signals
Self-hostable
Agent packet
Structured decision data for Future AGI
This packet is the compact machine-readable view agents should use before following source links or taking action.
Capabilities
automation, workflow
Constraints
open source, self hosted
Deployment
self hosted, cloud
Permission surface
Low explicit permission surface in metadata
Recommended workflows
Browser automation, Evaluation and observability, Reusable skill workflow
Overview
What Future AGI does
What it is
It combines traces, evals, simulations, datasets, gateway workflows, and guardrails in a self-hostable platform.
Why it matters
Agent quality needs structured measurement and operations loops before workflows reach real users.
How to evaluate it
Instrument one agent path, add evaluation datasets, and use traces and guardrails to inspect regressions.
Facts
Known metadata and operating surface
These fields are separated from editorial interpretation so agents can reason over facts and missing checks.
Resource type tool
Category Tools
Maturity active
Difficulty Unknown
License Apache-2.0
Pricing open source
Verified 2026-06-11
Source confidence high
Risk level low
Fit matrix
Where Future AGI fits in an agent stack
strong
Browser automation
Future AGI has multiple signals for browser automation, including matching tags, capabilities, category, or positioning.
- Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
strong
Evaluation and observability
Future AGI has multiple signals for evaluation and observability, including matching tags, capabilities, category, or positioning.
- Add one repeatable test case and confirm results can run again in review or CI.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
strong
Reusable skill workflow
Future AGI has multiple signals for reusable skill workflow, including matching tags, capabilities, category, or positioning.
- Run one skill end to end and check whether it produces evidence or structured output.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Coding agent workflow
Future AGI has at least one signal for coding agent workflow, but should be checked against a real task before adoption.
- Run a small repository change and inspect the diff, tests, and rollback path.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Local or private AI stack
Future AGI has at least one signal for local or private ai stack, but should be checked against a real task before adoption.
- Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Robotics or embodied agent workflow
Future AGI has at least one signal for robotics or embodied agent workflow, but should be checked against a real task before adoption.
- Separate simulator claims from hardware claims and verify safety boundaries before real-world operation.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs
What an agent should inspect
Likely inputs
- Repositories, files, issues, terminal output, and test results
- Official setup instructions and a small real workflow
Likely outputs
- Diffs, commits, explanations, test results, or review notes
- Scores, traces, regression results, dashboards, or failure cases
- A decision on whether this resource fits the target workflow
Evidence
Sources, claims, and missing checks
Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.
GitHub github
Repository source for code, license, issues, releases, and implementation details.
Homepage homepageOfficial or project-controlled source for this resource profile.
Future AGI is listed as open source.
License metadata: Apache-2.0Future AGI has a recorded GitHub repository: future-agi/future-agi.
Resource facts and GitHub source link.Future AGI supports these recorded deployment modes: self hosted, cloud.
OpenAgent decision signal metadata.Future AGI is tagged with automation, workflow capabilities.
OpenAgent capability taxonomy.- Dedicated docs link is missing.
- Repository freshness has not been recorded.
Next action
How to start evaluating Future AGI
Inspect repository
Check license, recent activity, issues, examples, and security-sensitive code paths.
Open sourceOpen Homepage
Start from the official source before adopting third-party instructions.
Open source Compare
Alternatives and nearby resources
Use related resources to compare category fit, license, deployment model, and first-workflow behavior.
FAQ
Common questions about Future AGI
Is Future AGI open source?
Yes. The GitHub repository is listed under the Apache-2.0 license.
Who should evaluate Future AGI?
Teams shipping production LLM or agent applications should evaluate it as an evaluation and observability layer.