Home/Compare/octocode vs semble

Comparison

octocode vs semble

Verdict

Pick octocode if octocode is an MCP server that uses LLM patterns for semantic code research and context generation in real-time; pick semble if semble is a Python-based tool that facilitates fast and accurate code search for AI agents with up to 98% fewer tokens compared to traditional grep+read methods.

Markdown twin · octocode alternatives · semble alternatives

GraphCanon updated 1d

octocode logo

octocode

bgauryy/octocode

900pushed Jul 25, 2026
vs
semble logo

semble

MinishLab/semble

5.9kpushed Aug 12, 2026

Trust & integrity

Signaloctocodesemble
Maintenance
Very active (1d since push)
As of 3w · github_public_v1
Active (10d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Personal account
As of 3w · github_public_v1
Not a fork · Organization account
As of 1d · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · 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

octocode
MCP server for semantic code research with LLM patterns
semble
Fast and Accurate Code Search for Agents

Stars

octocode
900
semble
5.9k

Forks

octocode
77
semble
256

Open issues

octocode
2
semble
3

Language

octocode
TypeScript
semble
Python

Adopt for

octocode
Octocode is an MCP server that uses LLM patterns for semantic code research and context generation in real-time.
semble
Semble is a Python-based tool that facilitates fast and accurate code search for AI agents with up to 98% fewer tokens compared to traditional grep+read methods.

Persona

octocode
-
semble
-

Runtime

octocode
-
semble
-

License

octocode
MIT
semble
MIT

Last pushed

octocode
Jul 25, 2026
semble
Aug 12, 2026

Categories

octocode
AI Agents, Data & Retrieval, LLM Frameworks
semble
AI Agents, Data & Retrieval

Trust and health

Maintenance

octocode
Very active (96%)
semble
Active (82%)

Days since push

octocode
1d
semble
10d

Open issues (now)

octocode
2
semble
3

Stars delta

octocode
Unknown
semble
+247 (30d)

Open issues delta

octocode
Unknown
semble
-4 (30d)

Owner type

octocode
User
semble
Organization

Full report

octocode
Trust report

Shared compatibility

  • Cursor · octocode: Works with Cursor · semble: Works with Cursor
  • VS Code · octocode: Works with VS Code · semble: Works with VS Code

Choose octocode if…

  • octocode is primarily TypeScript; semble is Python.
  • Tags unique to octocode: agent, ai-tools, code-intelligence, context.
  • Also covers LLM Frameworks.
  • When you need to search across both public and private repositories based on your user permissions.

When NOT to use octocode

  • If your use case does not require real-time semantic context generation from large language models (LLMs).
  • When you have no need for integrating with public and private repositories via their permissions system.

Choose semble if…

  • semble is primarily Python; octocode is TypeScript.
  • Requirements: Operating with Python, Semble does not require Docker for its operation..
  • Tags unique to semble: agents, embeddings, mcp, retrieval.
  • - Use Semble when you are specifically working with AI agents or models and require efficient, token-economical code search operations.

When NOT to use semble

  • - Avoid using Semble if your use case does not involve AI agents or the model-context-protocol (MCP). Competitor tools might offer better features tailored to non-agent-based code search.
  • - Not recommended in scenarios where token efficiency is not a concern, as competitors may provide more versatile functionalities without focusing on token reduction.

Explore

Sources

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

GitHub stars on cards: octocode 900 · semble 5.9k (synced Jul 27, 2026).

Common questions

What is the difference between octocode and semble?
octocode: MCP server for semantic code research with LLM patterns. semble: Fast and Accurate Code Search for Agents. See the comparison table for live GitHub stats and shared categories.
When should I choose octocode over semble?
Choose octocode over semble when octocode is primarily TypeScript; semble is Python; Tags unique to octocode: agent, ai-tools, code-intelligence, context; Also covers LLM Frameworks; When you need to search across both public and private repositories based on your user permissions.
When should I choose semble over octocode?
Choose semble over octocode when semble is primarily Python; octocode is TypeScript; Requirements: Operating with Python, Semble does not require Docker for its operation.; Tags unique to semble: agents, embeddings, mcp, retrieval; - Use Semble when you are specifically working with AI agents or models and require efficient, token-economical code search operations.
When should I avoid octocode?
If your use case does not require real-time semantic context generation from large language models (LLMs). When you have no need for integrating with public and private repositories via their permissions system.
When should I avoid semble?
- Avoid using Semble if your use case does not involve AI agents or the model-context-protocol (MCP). Competitor tools might offer better features tailored to non-agent-based code search. - Not recommended in scenarios where token efficiency is not a concern, as competitors may provide more versatile functionalities without focusing on token reduction.
Is octocode or semble more popular on GitHub?
semble has more GitHub stars (5,927 vs 900). Stars measure visibility, not whether either tool fits your constraints.
Are octocode and semble open source?
Yes - both are open-source projects on GitHub (octocode: MIT, semble: MIT).
Where can I find alternatives to octocode or semble?
GraphCanon lists graph-backed alternatives at octocode alternatives and semble alternatives (octocode markdown twin, semble 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, octocode or semble?
octocode: Very active. semble: 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 octocode and semble?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: octocode trust report; semble trust report.

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