Context7
Up-to-date docs for AI agents
제작자가 쓴 설명(영어 원문)
Local memory and context retrieval for AI agents through CueMap.
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": {
"cuemap": {
"command": "npx",
"args": [
"-y",
"cuemap-mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add cuemap -- npx -y cuemap-mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"cuemap": {
"command": "npx",
"args": [
"-y",
"cuemap-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"cuemap": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"cuemap-mcp"
]
}
}
}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 6일 점검
레지스트리 이름이 GitHub 계정 cuemap-dev 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(0.7.5)은 21일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 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
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CueMap MCP Server v0.7.5
A premium MCP bridge for explainable, repository-aware agent memory.
The Model Context Protocol (MCP) server for CueMap, allowing AI coding assistants (like Claude Desktop, Cursor, Windsurf, and Antigravity) to instantly recall codebase context using the CueMap engine.
For agent-facing operating guidance—including repository consent, supported content types, recall modes, accuracy-oriented knob selection, and troubleshooting—see SKILL.md.
The CueMap MCP Server is designed to work completely out-of-the-box. When started, it automatically manages a high-performance Rust instance of the CueMap Server in the background. The v0.7.3 engine bundles qint8 MiniLM-L3 by default and q4 MiniLM-L3 for the edge profile; no model download occurs at runtime.
You do not need to install or run the CueMap CLI manually. The correct pre-compiled binary for your operating system is automatically downloaded via optional NPM dependencies. Embedded startup supports Linux x64/ARM64, macOS x64/ARM64, and Windows x64.
# Global installation makes the `cuemap-mcp` command available
npm install -g cuemap-mcp
*(Note: Ensure your package manager is configured to download optionalDependencies so the local Rust binary is included).*
CueMap also ships a separate cuemap-agent-plugin package for Agent Plugins-compatible clients. It bundles the portable plugin.json manifest, stdio mcp.json configuration, and a repository-memory skill. The plugin launches this MCP server at the matching release version and must be installed or downloaded separately from cuemap-mcp.
By default, the embedded engine runs on port 8735. You can customize the server behavior by passing the following environment variables in your MCP configuration:
CUEMAP_PORT: Override the port the embedded engine binds to (default: 8735).CUEMAP_CONFIG_PATH: Absolute path to a custom server_config.toml to configure advanced Engine tuning, background jobs, and RAG search parameters.CUEMAP_URL: If you prefer to bypass the embedded engine and connect to a remotely hosted or separately running CueMap server, specify its URL here (e.g. http://localhost:8735).CUEMAP_PROJECT: Override the default project. Without this setting, CueMap derives a stable repository-scoped project from the current Git remote or working directory.CUEMAP_LOG_PATH: Override the embedded engine log path. It defaults to ~/.cuemap/server.log, which is the file read by cuemap logs.The MCP server calls EmbeddedCueMap.start() as soon as Codex launches the plugin process, before any CueMap tool is invoked. It attaches to a compatible engine already listening at CUEMAP_URL or the configured port; otherwise it starts and owns a local engine automatically. cuemap_init does not start the server—it previews or applies a confirmed repository scope after the engine is ready. An engine owned by the MCP process is stopped gracefully when that process exits.
To use this MCP server with your AI assistant, add it to your assistant's MCP configuration file.
{
"mcpServers": { "cuemap": { "command": "npx", "args": [ "-y", "cuemap-mcp" ], "env": { "CUEMAP_PORT": "8735" } } } }
path (string): Absolute path to the repository root.projectName (string, optional): Project ID override. Defaults to the stable repository-scoped ID.includedPaths (string[], optional): Repository-relative files or folders to preview. Empty means all supported files allowed by ignore rules.ignoredPatterns (string[], optional): Additional gitignore-style exclusions.ignoredExtensions (string[], optional): Additional excluded extensions.idle status with 0/0 writes is not considered complete.path (string): Absolute path to the repository root.projectName (string, optional): Project ID override. Defaults to the stable repository-scoped ID.includedPaths (string[], optional): User-approved repository-relative files or folders. Empty means all supported files allowed by ignore rules.ignoredPatterns (string[], optional): Additional gitignore-style exclusions.ignoredExtensions (string[], optional): Additional excluded extensions.confirmed (boolean): Must be true only after explicit user confirmation of the previewed scope.cuemap_init until verified_complete is true.project (string, optional): Project ID override. Defaults to the stable repository-scoped ID.active: Whether the current phase is non-terminal or writes/intent annotations remain pending.observed_activity: Whether this MCP process has observed an active phase or positive write/intent counts for the project.pending_writes: Remaining writes based on the latest totals.pending_intents: Remaining memory intent annotations based on the latest totals.verified_complete: True only after activity has been observed, the project reaches done or idle, no work failed or remains pending, and intent_ready is not false..cuemap package.global: true.memory_id and owning project. Requires an engine supporting GET /memories/:id?decoded=true; older engines return an upgrade error through this tool.cues.confirmed: true after explicit user confirmation.depth and same_domain_only controls.embeddings.These tools are for explicit ingestion requests. Repository initialization continues to use the preview, confirmation, and watcher workflow above.
confirmed: true.confirmed: true.content (string): Memory content to store.project (string, optional): Project ID that will own the memory. Defaults to the current repository-scoped project.cues (string[], optional): Explicit cues/tags to associate with the memory.metadata (object, optional): JSON metadata to store with the memory.source_key (string, optional): Stable source key for deterministic upsert/deduplication.event_time (number, optional): Original event timestamp as Unix seconds. Defaults to ingestion time.embedding (number[], optional): Precomputed memory embedding.disable_temporal_chunking (boolean, optional): Disable temporal chunking for this memory.async_ingest (boolean, optional): Process ingestion in the background and return immediately.target: "query" or "memory" and returns relative intent scores, recall/memory eligibility, confidence weight, and model/taxonomy versions. Scores are ranking signals, not calibrated probabilities.query (string): The natural language query to search for.limit (number, optional): Maximum results to return (default: 10).response_mode (full | preview, optional): Default full. Use preview for broad discovery; each hit returns a leading excerpt instead of full content, retaining IDs and metadata.preview_chars (integer, optional): Preview length cap, 100–2000 UTF-16 code units (default: 200). Ignored in full mode. Metadata and diagnostics are not capped.projects (string[], optional): List of project IDs to scope the search to. Multiple enables cross-project queries.cues (string[], optional): Specific cue tags to filter the search.query_time (string, optional): Timestamp or natural-language time anchor for v0.7 temporal query intent.depth (number, optional): Depth of multi-hop recall expander (default: 1).expansion_depth (number or "conversation_round", optional): Neighbor context expansion (default: "conversation_round"). Values above 1 include nearby parent chunks or source-ordered context, using a radius of expansion_depth - 1 when linkage exists. "conversation_round" prepends the message each result replies to (for an assistant reply, t앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요