CodeNib

ai.codenib由 codenib.ai 發布v0.2.5更新於 Nov 4, 2026

Source-linked CodeGraph exploration, ranked search, and static navigation for coding agents.

已驗證STDIO僅桌面知識與記憶開發者工具

概覽

AI 產生的概覽

CodeNib 為程式碼倉庫建立本機、可追溯至原始碼的程式碼圖譜,讓編碼助理能檢索排序後的程式碼脈絡並跳轉定義與參照。

可以做什麼
  • 檢索附檔案與行號參照的有限範圍程式碼脈絡
  • 跳轉定義與靜態參照,包含傳入與傳出關係
  • 一次呼叫取得相依子圖,深度最多 8 層
  • 為多種語言建立索引,圖後端涵蓋 Python、Go、Rust、C/C++、C#、Java、Ruby、PHP、Kotlin、Scala、JavaScript 與 TypeScript
  • 匯出附原始碼引用的倉庫 Wiki
適用情境
適合編碼助理在較大的多語言倉庫中定位某段行為的實作位置,並沿呼叫路徑追蹤超過一跳的關係,而不只依賴 grep 與逐一讀檔。對已在本機檢出程式碼上使用 Claude Code 或 Codex 的團隊最有用。
執行需求
以 stdio 在本機執行,需要 Python 3.10+、Git,以及 Claude Code 或 Codex。從 PyPI 安裝 codenib 的 graph 與 mcp 附加元件,再對每個倉庫執行 codegraph init 初始化。核心 CodeGraph 路徑不需要模型、API 金鑰或 GPU;各語言工具鏈與前置條件不同。
安裝前請注意
初始化會接受未提交的變更並保留檢出狀態,但應把索引與重建成本計入評估。靜態參照可能遺漏外部或動態關係,描述呼叫路徑前應先閱讀原始碼。可選的 grep 到 Jev 路線使用 OpenRouter,會把選取的程式碼傳送到遠端模型,該路線與免模型的核心功能相互獨立。專案處於 beta 階段,公開介面可能變動。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 CodeNib,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

[CodeNib]

Find the right code. Follow its references.

Give Claude Code and Codex source context and typed graph navigation across languages.

71.4% code-block Recall@5 on 100 real issues.
Model-planned grep → Jev: +12.8 percentage points over the same grep candidates without reranking.
Experimental result · Method and limitations

Use with your agent  ·  Browse a Wiki  ·  Languages  ·  Reproductions  ·  Releases

[CI] [PyPI version] [Latest GitHub Release] [arXiv paper] [Hugging Face: #1 Paper of the Day] [Apache 2.0 license]

[Play a recorded Claude Code session on Requests: explore_context finds where authentication is stripped on redirects, then one dependency_subgraph call traces the four-hop caller chain from the public API]

▶ Watch the 15-second replay · real CLI output · waits condensed · Pinned source, transcript and setup details.

New in 0.2.5: saved repository Wikis and portable OKF export, Pyrefly-backed Python graphs, static entry-path navigation and call-path rule checks. Read the release notes.

Quickstart

Requires Python 3.10+, Git, and Claude Code or Codex. Initialization accepts uncommitted edits and preserves the checkout.

bash
python -m pip install "codenib[graph,mcp]"codenib codegraph init /path/to/your/repo

Then ask your agent: “Use CodeNib's explore_context to find where request retry behavior is implemented. Cite the files and lines.”

This shipping path builds local search and a typed symbol graph, then connects installed agent clients. It needs no model, API key, or GPU for CodeNib; your agent uses its own model. It is separate from the grep/Jev experiment above. Language toolchain and project prerequisites vary.

Setup and troubleshooting · Source exclusions · All MCP tools · Local Wiki

Why CodeNib

  • Inspect the evidence. Retrieve bounded code context with file and line references, then navigate definitions and static references. Read the source at each reference before describing a call path.
  • Use the same tools across languages. The registry tracks 14 language entries, including 12 with graph backends. Check capability and setup differences in the language matrix.
  • Compare methods on the same source. Pinned agent contracts, datasets, and scorer checks make the reproduction surface inspectable.
  • Share what you found. Export a Wiki with source citations to your own GitHub Pages, or browse the public examples.

How it compares

What an agent can ask each tool. Peer interfaces were checked against upstream docs on 2026-09-28. This compares capabilities, not benchmark scores.

ToolAsk in plain languageRelationships beyond one hopRelationships resolved byRuns
grep / readNo; literal or regexNoText matchLocal
CodeNib CodeGraphYes; ranked source anchors (explore_context)Incoming/outgoing static references; one dependency_subgraph call, depth ≤ 8SCIP/LSP indexers (compiler-resolved)Local
SerenaNo; symbol name or regexOne level per call (find_referencing_symbols)Live language server or IDELocal
CodeGraph (colbymchenry)Yes; FTS5 full-text (codegraph_explore)Yes; call paths in codegraph_exploreTree-sitter AST extractionLocal; telemetry opt-out
DeepWiki public MCPYes; generated answers (ask_question)No structured graph toolsGenerated WikiHosted

CodeNib's indexed references can include calls, fields, type uses and function values. Inspect the source to establish which references invoke a function; external and dynamic relationships may be missing. For a known string or file, your agent's native search and reads remain useful. Include indexing and rebuild costs when assessing graph navigation on your own tasks.

None of these repository tools needs its own model or API key; your agent uses its own model. Detailed comparison, sources and boundaries. CodeNib also includes an optional grep → Jev route using OpenRouter for planning and reranking; selected code goes to remote models. Authorization previews remain opt-in. The historical research result above is separate from the product evaluation and the model-free CodeGraph row.

Languages

Graph backends: Python, Go, Rust, C/C++, C#, Java, Ruby, PHP, Kotlin, Scala, JavaScript, and TypeScript. Swift and Lua support chunking/retrieval. Provider prerequisites and coverage differ by language.

The generated language matrix separates chunking, graph backends, incremental-backend support, and decoder parity. The product currently reuses or rebuilds views; file-level delta repair is not enabled.

Results and reproductions

Start hereWhat you can inspect
Context methods and support matrixEvery retrieval pipeline, LLM workflow and agent route, sorted by the views it reads and who controls the search
BenchmarksLocalization, agent-context and resolution layers, evidence levels, and the method × benchmark matrix over CodeNib Base/Synthesis, SWE-bench Lite, Loc-Bench, SWE-Explore, Agent Retrieval Bench and ContextBench
grep → Jev result100-issue retrieval comparison, candidate controls, model use and limitations
Agent integration matrixRevision-pinned LocAgent, Agentless, CoSIL, OrcaLoca and RepoNavigator contracts; compatibility does not imply reproduced paper scores
SWE-Explore validation1,020/1,020 real-output metric cells match the pinned official evaluator on a fixed 20-case run
DGX Spark deploymentLocal Wiki, CodeGraph and model serving on GB10; a deployment guide, not a token-saving benchmark

Documentation and community

Documentation · Architecture · Contributing · CI and testing · Changelog · Discord

CodeNib is in beta; public interfaces may change before a stable release. Historical research artifacts retain their published dataset identifiers.

Citation

If you use CodeNib in your research, please cite our arXiv paper:

bibtex
@misc{yu2026codenibmultiviewdataserving,      title={CodeNib: A Multi-View Data System for Serving Repository Context to Coding Agents},      author={Zhongming Yu and Hengjia Yu and Boqin Yuan and Shuting Zhao and Yizhao Chen and Aryan Dokania and Mihir Jagtap and Jiayu Chang and Yitong Ma and Yash Jayswal and Wentao Ni and Hejia Zhang and Zhaoling Chen and Gangda Deng and Jishen Zhao},      year={2026},      eprint={2607.25431},      archivePrefix={arXiv},      primaryClass={cs.SE},      url={https://arxiv.org/abs/2607.25431},}

CodeNib is licensed under Apache 2.0.

來源:README.md,提交 35f2fea

工具

0
SourceWeft 曾在隔離沙箱中以無憑證方式啟動該軟體包一次,以列出其工具,但未能完成:伺服器未能啟動。

版本歷史

3
  1. v0.2.5最新Nov 4, 2026
  2. v0.2.4Sep 27, 2026
  3. v0.2.3Sep 16, 2026

評分

已滿足適用檢查項的 50%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通25 分

    請保持端點能夠回應 MCP 握手;SourceWeft 每 30 天探測一次。

  • 已宣告認證方式10 分

    請在註冊中心條目中宣告憑證請求標頭,或保持端點能夠回應探測,以便判定其認證方式。

  • 已列出工具15 分

    請讓伺服器在無憑證時回應 tools/list,或發布可在沙箱中無憑證啟動的軟體包。

  • 描述必需15 分
  • 圖示10 分
  • 文件15 分
  • 授權條款10 分