Comparison
Agent-Reach vs fastembed
Verdict
Pick Agent-Reach when license: Agent-Reach is MIT, fastembed is Apache-2.0; pick fastembed when license: fastembed is Apache-2.0, Agent-Reach is MIT.
Markdown twin · Agent-Reach alternatives · fastembed alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | Agent-Reach | fastembed |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Active (18d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No MCP manifest As of today · mcp_manifest | No lockfile As of today · none |
Tagline
- 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.
- fastembed
- Fast, Accurate, Lightweight Python library to make State of the Art Embedding
Stars
- Agent-Reach
- 55k
- fastembed
- 3.1k
Forks
- Agent-Reach
- 4.5k
- fastembed
- 213
Open issues
- Agent-Reach
- 144
- fastembed
- 137
Language
- Agent-Reach
- Python
- fastembed
- Python
Adopt for
- Agent-Reach
- -
- fastembed
- -
Persona
- Agent-Reach
- -
- fastembed
- -
Runtime
- Agent-Reach
- -
- fastembed
- -
License
- Agent-Reach
- MIT
- fastembed
- Apache-2.0
Last pushed
- Agent-Reach
- Jul 10, 2026
- fastembed
- Jun 23, 2026
Categories
- Agent-Reach
- AI Agents, LLM Frameworks, Developer Tools
- fastembed
- LLM Frameworks, Data & Retrieval, Vector Databases
Trust and health
Maintenance
- Agent-Reach
- Very active (96%)
- fastembed
- Active (82%)
Days since push
- Agent-Reach
- 0d
- fastembed
- 18d
Open issues (now)
- Agent-Reach
- 144
- fastembed
- 137
Owner type
- Agent-Reach
- User
- fastembed
- Organization
Security scan
- Agent-Reach
- No MCP manifest
- fastembed
- No lockfile
Full report
- Agent-Reach
- Trust report
- fastembed
- Trust report
Choose Agent-Reach if…
- License: Agent-Reach is MIT, fastembed is Apache-2.0.
- Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code.
- Also covers AI Agents, Developer Tools.
When NOT to use Agent-Reach
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
Choose fastembed if…
- License: fastembed is Apache-2.0, Agent-Reach is MIT.
- Tags unique to fastembed: embeddings, python, rag, retrieval-augmented-generation.
- Also covers Data & Retrieval, Vector Databases.
When NOT to use fastembed
- 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.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
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 Jul 11, 2026
- GitHub forks (Panniantong/Agent-Reach) · observed Jul 11, 2026
- Last push (Panniantong/Agent-Reach) · observed Jul 10, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (qdrant/fastembed) · observed Jul 11, 2026
- GitHub forks (qdrant/fastembed) · observed Jul 11, 2026
- Last push (qdrant/fastembed) · observed Jun 23, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Agent-Reach 55k · fastembed 3.1k (synced Jul 11, 2026).
Common questions
- What is the difference between Agent-Reach and fastembed?
- 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.. fastembed: Fast, Accurate, Lightweight Python library to make State of the Art Embedding. See the comparison table for live GitHub stats and shared categories.
- When should I choose Agent-Reach over fastembed?
- Choose Agent-Reach over fastembed when License: Agent-Reach is MIT, fastembed is Apache-2.0; Tags unique to Agent-Reach: agent-infrastructure, ai-search, bilibili, claude-code; Also covers AI Agents, Developer Tools.
- When should I choose fastembed over Agent-Reach?
- Choose fastembed over Agent-Reach when License: fastembed is Apache-2.0, Agent-Reach is MIT; Tags unique to fastembed: embeddings, python, rag, retrieval-augmented-generation; Also covers Data & Retrieval, Vector Databases.
- When should I avoid Agent-Reach?
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
- When should I avoid fastembed?
- 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. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Is Agent-Reach or fastembed more popular on GitHub?
- Agent-Reach has more GitHub stars (54,715 vs 3,085). Stars measure visibility, not whether either tool fits your constraints.
- Are Agent-Reach and fastembed open source?
- Yes - both are open-source projects on GitHub (Agent-Reach: MIT, fastembed: Apache-2.0).
- Where can I find alternatives to Agent-Reach or fastembed?
- GraphCanon lists graph-backed alternatives at Agent-Reach alternatives and fastembed alternatives (Agent-Reach markdown twin, fastembed 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 fastembed?
- Agent-Reach: Very active. fastembed: 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 fastembed?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Agent-Reach trust report; fastembed trust report.