GraphCanon
Home/Compare/FEDOT vs Agent-Reach

Comparison

FEDOT vs Agent-Reach

Verdict

Pick FEDOT when license: FEDOT is BSD-3-Clause, Agent-Reach is MIT; pick Agent-Reach when license: Agent-Reach is MIT, FEDOT is BSD-3-Clause.

Markdown twin · FEDOT alternatives · Agent-Reach alternatives

GraphCanon updated today

FEDOT logo

FEDOT

aimclub/FEDOT

★ 709pushed Jul 8, 2026
vs
Agent-Reach logo

Agent-Reach

Panniantong/Agent-Reach

★ 55kpushed Jul 10, 2026

Trust & integrity

SignalFEDOTAgent-Reach
Maintenance
Very active (3d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
27 low (27 low)
As of today · osv@v1
No MCP manifest
As of today · mcp_manifest
FEDOT trust reportAgent-Reach trust reportTrust methodology

Tagline

FEDOT
Automated modeling and machine learning framework FEDOT
Agent-Reach
Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.

Stars

FEDOT
709
Agent-Reach
55k

Forks

FEDOT
92
Agent-Reach
4.5k

Open issues

FEDOT
83
Agent-Reach
144

Language

FEDOT
Python
Agent-Reach
Python

Adopt for

FEDOT
-
Agent-Reach
-

Persona

FEDOT
-
Agent-Reach
-

Runtime

FEDOT
-
Agent-Reach
-

License

FEDOT
BSD-3-Clause
Agent-Reach
MIT

Last pushed

FEDOT
Jul 8, 2026
Agent-Reach
Jul 10, 2026

Categories

FEDOT
LLM Frameworks, Data & Retrieval, Computer Vision
Agent-Reach
LLM Frameworks, AI Agents, Developer Tools

Trust and health

Days since push

FEDOT
3d
Agent-Reach
0d

Open issues (now)

FEDOT
83
Agent-Reach
144

Owner type

FEDOT
Organization
Agent-Reach
User

Security scan

FEDOT
27 low (27 low)
Agent-Reach
No MCP manifest

Full report

FEDOT
Trust report
Agent-Reach
Trust report

Choose FEDOT if…

  • License: FEDOT is BSD-3-Clause, Agent-Reach is MIT.
  • Tags unique to FEDOT: automl, evolutionary-algorithms, genetic-programming, machine-learning.
  • Also covers Data & Retrieval, Computer Vision.

When NOT to use FEDOT

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
GitHubDetails

Choose Agent-Reach if…

  • License: Agent-Reach is MIT, FEDOT is BSD-3-Clause.
  • Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
  • Also covers AI Agents, Developer Tools.

When NOT to use Agent-Reach

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
GitHubDetails

Explore

FEDOT trust report →Agent-Reach trust report →LLM Frameworks category →Data & Retrieval category →Computer Vision category →AI Agents category →Developer Tools category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: FEDOT 709 · Agent-Reach 55k (synced Jul 11, 2026).

Common questions

What is the difference between FEDOT and Agent-Reach?
FEDOT: Automated modeling and machine learning framework FEDOT. Agent-Reach: Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.. See the comparison table for live GitHub stats and shared categories.
When should I choose FEDOT over Agent-Reach?
Choose FEDOT over Agent-Reach when License: FEDOT is BSD-3-Clause, Agent-Reach is MIT; Tags unique to FEDOT: automl, evolutionary-algorithms, genetic-programming, machine-learning; Also covers Data & Retrieval, Computer Vision.
When should I choose Agent-Reach over FEDOT?
Choose Agent-Reach over FEDOT when License: Agent-Reach is MIT, FEDOT is BSD-3-Clause; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents, Developer Tools.
When should I avoid FEDOT?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
When should I avoid Agent-Reach?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
Is FEDOT or Agent-Reach more popular on GitHub?
Agent-Reach has more GitHub stars (54,715 vs 709). Stars measure visibility, not whether either tool fits your constraints.
Are FEDOT and Agent-Reach open source?
Yes - both are open-source projects on GitHub (FEDOT: BSD-3-Clause, Agent-Reach: MIT).
Where can I find alternatives to FEDOT or Agent-Reach?
GraphCanon lists graph-backed alternatives at FEDOT alternatives and Agent-Reach alternatives (FEDOT markdown twin, Agent-Reach markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, FEDOT or Agent-Reach?
FEDOT: Very active. Agent-Reach: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for FEDOT and Agent-Reach?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: FEDOT trust report; Agent-Reach trust report.