Comparison
Agent-Reach vs SAM
Verdict
Pick Agent-Reach if agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content; pick SAM if sAM is an AI assistant for macOS systems with Apple Silicon built in Swift and supports local LLM models, offering installation via Homebrew.
Markdown twin · Agent-Reach alternatives · SAM alternatives
GraphCanon updated Sep 20, 2026
vs
Trust & integrity
| Signal | Agent-Reach | SAM |
|---|---|---|
| Maintenance | Very active (4d since push) As of Sep 20, 2026 · github_public_v1 | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- Agent-Reach
- AI Agent for Automated Web and Social Media Data Extraction
- SAM
- An AI assistant for everyone
Stars
- Agent-Reach
- 84k
- SAM
- 130
Forks
- Agent-Reach
- 7.3k
- SAM
- 6
Open issues
- Agent-Reach
- 153
- SAM
- 0
Language
- Agent-Reach
- Python
- SAM
- Swift
Adopt for
- Agent-Reach
- Agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content.
- SAM
- SAM is an AI assistant for macOS systems with Apple Silicon built in Swift and supports local LLM models, offering installation via Homebrew.
Persona
- Agent-Reach
- -
- SAM
- -
Runtime
- Agent-Reach
- -
- SAM
- -
License
- Agent-Reach
- MIT
- SAM
- GPL-3.0
Last pushed
- Agent-Reach
- Sep 15, 2026
- SAM
- Sep 19, 2026
Categories
- Agent-Reach
- AI Agents, Data & Retrieval
- SAM
- AI Agents, LLM Frameworks
Trust and health
Days since push
- Agent-Reach
- 4d
- SAM
- 1d
Open issues (now)
- Agent-Reach
- 153
- SAM
- 0
Stars delta
- Agent-Reach
- +23k (30d)
- SAM
- 0 (30d)
Open issues delta
- Agent-Reach
- -15 (30d)
- SAM
- 0 (30d)
Owner type
- Agent-Reach
- User
- SAM
- Organization
Full report
- Agent-Reach
- Trust report
- SAM
- Trust report
Choose Agent-Reach if…
- Agent-Reach is primarily Python; SAM is Swift.
- License: Agent-Reach is MIT, SAM is GPL-3.0.
- Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation.
- Also covers Data & Retrieval.
- When needing to bypass costly API fees for extensive social media platform data extraction
When NOT to use Agent-Reach
- If strict compliance with website scraping policies is critical due to its use of scraping techniques
- When direct interaction through APIs for precision and reliability is preferred over scraping
Choose SAM if…
- SAM is primarily Swift; Agent-Reach is Python.
- License: SAM is GPL-3.0, Agent-Reach is MIT.
- Requirements: Min 4 GB RAM; For optimal use with local AI models, a system with 16GB+ RAM is recommended.; The system should be equipped with macOS 14.0 (Sonoma) or later..
- Tags unique to SAM: ai-assistants, apple-silicon, open-source.
- Also covers LLM Frameworks.
- You should use SAM when you are working on a macOS system equipped with Apple Silicon as it is optimized for such hardware.
When NOT to use SAM
- Avoid using SAM if you are developing on an Intel-based Mac or any system running a different operating system as it is specifically designed for macOS and Apple Silicon.
- Do not opt for SAM if your project requires low memory consumption, because supporting local AI models typically demands high RAM (16GB+) and significant disk space.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Panniantong/Agent-Reach) · observed Sep 20, 2026
- GitHub forks (Panniantong/Agent-Reach) · observed Sep 20, 2026
- Last push (Panniantong/Agent-Reach) · observed Sep 15, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (SyntheticAutonomicMind/SAM) · observed Sep 20, 2026
- GitHub forks (SyntheticAutonomicMind/SAM) · observed Sep 20, 2026
- Last push (SyntheticAutonomicMind/SAM) · observed Sep 19, 2026
- License file (GPL-3.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: Agent-Reach 84k · SAM 130 (synced Sep 20, 2026).
Common questions
- What is the difference between Agent-Reach and SAM?
- Agent-Reach: AI Agent for Automated Web and Social Media Data Extraction. SAM: An AI assistant for everyone. See the comparison table for live GitHub stats and shared categories.
- When should I choose Agent-Reach over SAM?
- Choose Agent-Reach over SAM when Agent-Reach is primarily Python; SAM is Swift; License: Agent-Reach is MIT, SAM is GPL-3.0; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers Data & Retrieval; When needing to bypass costly API fees for extensive social media platform data extraction.
- When should I choose SAM over Agent-Reach?
- Choose SAM over Agent-Reach when SAM is primarily Swift; Agent-Reach is Python; License: SAM is GPL-3.0, Agent-Reach is MIT; Requirements: Min 4 GB RAM; For optimal use with local AI models, a system with 16GB+ RAM is recommended.; The system should be equipped with macOS 14.0 (Sonoma) or later.; Tags unique to SAM: ai-assistants, apple-silicon, open-source; Also covers LLM Frameworks; You should use SAM when you are working on a macOS system equipped with Apple Silicon as it is optimized for such hardware.
- When should I avoid Agent-Reach?
- If strict compliance with website scraping policies is critical due to its use of scraping techniques When direct interaction through APIs for precision and reliability is preferred over scraping
- When should I avoid SAM?
- Avoid using SAM if you are developing on an Intel-based Mac or any system running a different operating system as it is specifically designed for macOS and Apple Silicon. Do not opt for SAM if your project requires low memory consumption, because supporting local AI models typically demands high RAM (16GB+) and significant disk space.
- Is Agent-Reach or SAM more popular on GitHub?
- Agent-Reach has more GitHub stars (83,516 vs 130). Stars measure visibility, not whether either tool fits your constraints.
- Are Agent-Reach and SAM open source?
- Yes - both are open-source projects on GitHub (Agent-Reach: MIT, SAM: GPL-3.0).
- Where can I find alternatives to Agent-Reach or SAM?
- GraphCanon lists graph-backed alternatives at Agent-Reach alternatives and SAM alternatives (Agent-Reach markdown twin, SAM 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, Agent-Reach or SAM?
- Agent-Reach: Very active. SAM: 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 Agent-Reach and SAM?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Agent-Reach trust report; SAM trust report.