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เปิดจากผู้เผยแพร่
📖 Full manual at mareurs.github.io/codescout — installation, agent integrations, every tool, every concept.
Works with Claude Code, GitHub Copilot, Cursor, and any MCP-capable agent.
symbols, references, symbol_at, call_graph, edit_code, backed by LSP across 9 languagesworkspace.toml for cross-project navigation with per-project memory and indexingcargo build
./target/debug/codescout start --project /path/to/code
Register as an MCP server in ~/.claude/settings.json:
{
"mcpServers": {
"codescout": {
"command": "codescout",
"args": ["start", "--project", "."]
}
}
}
Onboarding is essential. Run
onboarding()once per project on first connect — it discovers languages, reads key files, and generates a project-specific system prompt and memory files. Without it, the agent navigates blind.Tip: Install the codescout-companion plugin to auto-steer Claude toward codescout tools in every session — including subagents.
→ Full setup, agent configs, and project-toml options: mareurs.github.io/codescout
codescout now embeds librarian — a workspace-wide artifact registry that indexes the markdown around your code (specs, plans, ADRs, runbooks, memories, audits, handoffs, roadmaps, user docs), stores metadata + a typed link graph in SQLite, and exposes it to the agent as queryable structured data instead of opaque file listings.
Why it matters. The code is half the project. The other half lives in
markdown files scattered across docs/, design notes, and runbooks. Without
indexing them, the agent re-discovers project history every session. With
librarian, "find every active spec touching the embedder" is a single tool call.
How it works.
~/.local/share/librarian/catalog.db.supersedes, implements, references, ...) connects
artifacts; walk it transitively with artifact(action="graph").project → repo → umbrella → all) lets the
agent widen beyond the current sub-project on demand.LIBRARIAN_EMBED_* turns
artifact(action="find", semantic="…") into vector search.How to use it.
# Find every active spec touching the retrieval stack
artifact(action="find", kind="spec", status="active", semantic="retrieval pipeline")
# Read one, with its outgoing link graph
artifact(action="get", id="abc123", include_links=true)
# Connect a plan to the spec it implements
artifact(action="link", src_id="<plan>", dst_id="<spec>", rel="implements")
# Pack a topic neighbourhood into a single markdown bundle for context
librarian(action="context", topic="hybrid sparse + dense retrieval", max_tokens=4000)
Trackers — augment any artifact with a persistent prompt + params, and codescout auto-refreshes it on demand. Friction logs, observation tables, sprint roadmaps — written once, maintained across sessions.
Embedded by default. No separate server to install. Opt out with
LIBRARIAN_ENABLED=0 for a leaner tool surface.
→ Full artifact guide: librarian embedded · trackers · time-travel · augmentation templates
semantic_search runs through an external Docker Compose stack (Qdrant +
dense embedder + SPLADE sparse + cross-encoder rerank). Two profiles: cpu
and gpu.
docker compose --profile cpu --env-file .env.cpu up -d
# or --profile gpu --env-file .env.gpu
set -a; source .env.cpu; set +a
cargo run --release --bin sync_project -- . codescout
codescout's design is informed by research on compound error in multi-agent systems — failure rates of 41–87% in production pipelines. This drove the choice of single-session skill-based workflows over agent orchestration chains. Read the analysis →
codescout's prompt surfaces — Iron Laws, get_guide topics, tracker rendering,
result envelopes — are shaped by measured findings on how coding agents trust,
follow, and resist the content a tool surfaces. The short version: authority framing
(a persona, a "trusted" marker) buys nothing; placement and server-computed
provenance buy everything. Trust attaches to what the server computes
(symbols, git state, freshness keys), never to a marker the content carries about
itself — because anything in a file body is forgeable by whoever wrote the file.
Read the findings →
Kotlin and Rust LSPs are expensive to boot and allow only one process per
workspace. codescout ships per-language multiplexers — a detached codescout mux process shares one LSP across all codescout instances. Cold-start happens
once; subsequent sessions connect instantly. No configuration needed.
Symbol navigation · File operations · Shell · Semantic search · Memory · Library navigation · Artifacts · Workflow & Config
Supported languages: Rust, Python, TypeScript/JavaScript, Go, Java, Kotlin, C/C++, C#, Ruby.
New features land on experiments before reaching master. They may change
or be removed without notice.
See CONTRIBUTING.md. PRs from Claude Code are welcome.
High-performance coding agent toolkit MCP server — IDE-grade code intelligence for LLMs
เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
Codescout ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-10-27 High-performance coding agent toolkit MCP server — IDE-grade code intelligence for LLMs