Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Persistent code knowledge graph + 9 composite MCP tools for AI coding agents.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"forensic-deepdive": {
"command": "uvx",
"args": [
"forensic-deepdive",
"serve",
"--repo",
"."
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add forensic-deepdive -- uvx forensic-deepdive serve --repo .프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"forensic-deepdive": {
"command": "uvx",
"args": [
"forensic-deepdive",
"serve",
"--repo",
"."
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"forensic-deepdive": {
"type": "stdio",
"command": "uvx",
"args": [
"forensic-deepdive",
"serve",
"--repo",
"."
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 Dhevenddra 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.10.0)은 3개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
`forensic-deepdive` gives an AI coding agent forensic understanding of an unfamiliar codebase — a persistent knowledge graph, an MCP server, and five durable markdown artifacts, so your agent stops re-discovering the same architecture from scratch every session.
uv tool install forensic-deepdive && forensic extract /path/to/repo
Why this is different: every edge and every emitted claim carries a confidence tag — EXTRACTED (deterministic fact) / INFERRED (a heuristic resolved cleanly) / AMBIGUOUS (multiple candidates, shown, not guessed) — so your agent knows what to trust *before* it acts on it. Nothing else in this category tags confidence at all.
| forensic-deepdive | GitNexus | CodeGraphContext | DeepWiki | Sourcegraph | |
|---|---|---|---|---|---|
| License | Apache-2.0 | PolyForm Noncommercial | MIT | proprietary (open variant: MIT) | partial |
| Persistent code knowledge graph | ✅ LadybugDB | ✅ LadybugDB | partial | ❌ | partial |
| MCP server | ✅ 9 composite tools | ✅ 16 tools | partial | ❌ | ❌ |
| Per-edge confidence taxonomy | ✅ EXTRACTED / INFERRED / AMBIGUOUS | ❌ | ❌ | ❌ | ❌ |
| Git archaeology as a first-class layer | ✅ | ❌ | ❌ | ❌ | partial |
| Durable committed markdown artifacts | ✅ 5 files | partial | partial | ✅ (wiki) | ❌ |
Agent-insight layer (record_insight / recall_insights) | ✅ | ❌ | ❌ | ❌ | ❌ |
| Multi-platform skill emission | ✅ 10 shims | partial | partial | ❌ | ❌ |
| Local-only (no cloud required) | ✅ co-equal | ✅ | ✅ | ❌ | ❌ |
GitNexus is the runaway leader in this category — but its PolyForm Noncommercial license locks every commercial user out. forensic-deepdive is the Apache-2.0 alternative: same persistent-graph-plus-MCP shape, plus honest confidence tags, git archaeology, persistent agent memory, and the 5 markdown artifacts as a fallback for any agent that doesn't speak MCP — with a license your employer's legal team will actually sign off on.
forensic-deepdive analyzes any codebase (9 languages, polyglot) and produces:
/.deepdive/graph.lbug — File, Symbol, Module, Commit, Author, Endpoint, and DbTable nodes plus DEFINES, MEMBER_OF, IMPORTS, CALLS, EXTENDS, IMPLEMENTS, TOUCHED_BY_COMMIT, AUTHORED_BY, CO_CHANGES_WITH, and the cross-boundary HANDLES / CALLS_ENDPOINT / ROUTES_TO / INJECTS / PERSISTS_TO edges. Every edge carries a confidence tag (EXTRACTED / INFERRED / AMBIGUOUS) — no hidden heuristics. The single Endpoint join node unifies five cross-boundary protocols (HTTP, MCP tools, registry-dispatch, gRPC, messaging/AMQP), so a frontend call resolves to its backend handler across the stack as one ROUTES_TO edge.forensic serve) exposing 9 composite tools (impact, context, archaeology, flow, query, record_insight, recall_insights, visualize, trace) consumable by Claude Code, Cursor, Codex, Continue, Cline, Windsurf — and any other MCP-aware agent. /docs/codebase/, regenerated from the graph on every extract:CLAUDE.md for any project.CLAUDE.md, AGENTS.md, .cursor/rules/codebase.mdc, .continue/rules/codebase.md), 5 single-intent Claude skills under .claude/skills/codebase-{exploring,debugging,impact-analysis,refactoring,onboarding}/, and a .claude-plugin/plugin.json manifest. All write-if-absent — hand-edited files are never overwritten.record_insight / recall_insights MCP tools backed by /.deepdive/insights.jsonl by default (zero dependencies, human-readable, git-friendly). The optional [graphiti] extra upgrades to a temporal knowledge graph backend above a 2-of-5 repo-size threshold.Extract also regenerates `ARCHITECTURE.md` — a system-level Mermaid view of the cross-boundary graph (ROUTES_TO / INJECTS / PERSISTS_TO, confidence-styled), a *separate human-validation surface* (not one of the five contract artifacts, exactly like forensic visualize and serve --ui). Regenerate it on its own with forensic diagram --repo . Use it to sanity-check the graph — a wrong edge there is a wrong edge everywhere.
Add `--emit-vault` to also write an Obsidian-friendly vault under /vault/ — every artifact gets summary:/tags: frontmatter, cross-references become [[wikilinks]], and an INDEX.md MOC ties them together (with a .obsidian/ config). A local-first second brain for humans (graph view, backlinks) and agents (triage by summary: without opening files, a traversable index). Opt-in; off by default.
v0.10.0 "The Upgrade Path" — an integrity release. v0.9 shipped correct, and then its findings run caught --refresh-shims being structurally unable to refresh half its targets, with 909 tests green over it. The cause wasn't the fix — it was that **every test in the suite wrote into an empty directory, so only the *first* run had ever been tested.** Everyone who isn't a new user lives on the untested path.
So 0.10 adds almost no surface. It makes the guarantees already made real: running Deepdive over a repo that already carries a previous release's output now provably converges (and provably leaves your hand-edited files alone), extract tells you when generated shims are stale instead of waiting for you to know the flag exists, and a stale examples/ fails CI rather than being caught by eye mid-release. New: forensic extract --timings, per-phase wall clock.
It also contains a cancelled feature, which is the more useful story. The planned performance work targeted PageRank. The profile required before touching it measured PageRank at 0.04 % of a large extract, and the *already-batched* store writes at 79–87 %. The optimization was disproven before it was written — see docs/findings/v0.10/PROFILE.md. Confirming a known technique had been applied had been mistaken for confirming it was fast.
The engine, the graph, the contract layer and the 5-artifact + 9-MCP-tool contract are unchanged from 0.9, and emitted content is byte-identical but for the version footer.
⚠ If you installed 0.8.0 or 0.9.0 and `forensic serve` stopped working — this is why. Those
releases declare
mcp>=1.27.1with no upper bound.mcp2.0.0 removedmcp.server.fastmcp,
which the MCP server imports, so a fresh install of 0.8.0 or 0.9.0 today resolves to
mcp
2.0.0 and fails on import. Our development lockfile pinned 1.27.1, so every local check stayed
green and only the clean-environment wheel smoke in CI could see it. Fix: upgrade to 0.10.0
(which caps
mcp<2), or pinmcp<2yourself. Nothing else about those releases is affected.
What's proven, and what isn't — the honest-framing section moved to docs/findings/HONEST.md (unchanged content, DEC-119). Short version: proven usable with real agent auto-discovery; not proven to make autonomous issue resolution measurably faster end-to-end (hardware-gated). This is an assisted-analysis tool, and it is not overclaimed as more.
# install from PyPI (puts `forensic` on PATH); or run ephemerally with uvx
uv tool install forensic-deepdive forensic info # banner + capability panel forensic extract /path/to/repo
git clone https://github.com/Dhevenddra/forensic-deepdive && cd forensic-deepdive uv sync --all-extras
uv run forensic info
uv run forensic onboard --repo /path/to/repo
uv run forensic extract /path/to/repo
uv run forensic trace --repo /path/to/repo
uv run forensic repl --repo /path/to/repo
uv run forensic browse --repo /path/to/repo
uv run deepdive --repo /path/to/repo
uv run forensic serve --repo /path/to/repo
uv run forensic list
Published as [`forensic-deepdive`](https://pypi.org/project/forensic-deepdive/) — no clone needed:
uv tool install forensic-deepdive # puts `forensic` on PATH
forensic extract /path/to/repo
uvx forensic-deepdive extract /path/to/repo
Optional extras: uv tool install "forensic-deepdive[semantic]" (offline ONNX NL query), [interactive] (the forensic repl query console, the forensic browse TUI graph browser, and the deepdive session shell), [openapi] (YAML spec parsing), [graphiti] (temporal insight backend).
Re-run extract with --refresh-shims once. The generated shims and skills under .claude/, .cursor/ and .continue/ are written only if absent, so a plain re-extract leaves your 0.8-era copies in place, and two of the skill files still cite internal decision IDs that 0.9 removed:
forensic extract /path/to/repo --force --refresh-shims
Only files Deepdive generated are rewritten. A shim you have hand-edited is never touched. pip install forensic-deepdive works too if you're not on uv.
forensic serve is a stdio MCP server exposing the 9 composite tools to any MCP-aware agent (Claude Code, Cursor, VS Code/Copilot, Codex, Continue, Cline, Windsurf). First build the graph once (forensic extract ), then wire the server. Three ways, easiest first:
1. Claude Code plugin (self-hosted marketplace — no PyPI step):
/plugin marketplace add Dhevenddra/forensic-deepdive
/plugin install forensic-deepdive@dhevenddra
2. From the [MCP Registry](https://registry.modelcontextprotocol.io) — indexed as io.github.Dhevenddra/forensic-deepdive, so registry-aware clients and discovery hubs (PulseMCP, MCPJungle, the VS Code @mcp index) can find and install it directly.
**3. Ma
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요