Potencia tu agente
Instalación del publicador. No es un endpoint de PlugMCP.
Host a copy with our keys and logs.
Aún no hay una versión empaquetada en el registro. Sigue el README del repositorio.
¿URL remota o un comando en tu máquina? En qué se diferencian las dos instalaciones
Ejecutar en PlugMCP
A new server you create. It is not this listing's official endpoint. Use the publisher install when you want their URL and their credentials.
AbrirCode intelligence AI agents can trust — correct cross-language structure across the supported language inventory, agent-native (MCP + CLI).
TSA indexes your codebase with tree-sitter and serves correct call graphs, symbol search, and structural queries to AI coding agents — locally, with no telemetry.
Why it's different:
Upgrading from v1.x? See docs/MIGRATION.md.
Requires Python 3.10+ (check:
python3 --version). Install from python.org if needed.
curl -fsSL https://raw.githubusercontent.com/aimasteracc/tree-sitter-analyzer/main/install.sh | bash
Auto-installs uv if missing, detects Claude Desktop / Claude Code / Cursor / VS Code, and writes the MCP entry. Run tree-sitter-analyzer --doctor to verify.
Bootstrap trust: for convenience, the command above downloads and executes the official
uvinstaller whenuvis missing or outdated. That installer is mutable and not content-bound; TSA warns before downloading it to a temporary file over TLS and performs a strict post-install version check. To avoid this unverified bootstrap, installuv >= 0.11.0manually first, or use the secure opt-out (which exits with manual-install instructions when bootstrap is needed):curl -fsSL https://raw.githubusercontent.com/aimasteracc/tree-sitter-analyzer/main/install.sh \ | TSA_DISABLE_UNVERIFIED_UV_BOOTSTRAP=1 bash
Install command for Claude Code:
claude mcp add tree-sitter-analyzer \
--env TREE_SITTER_PROJECT_ROOT="$PWD" \
-- uvx --from "tree-sitter-analyzer[mcp]" tree-sitter-analyzer-mcp
Restart your agent, then say: "Run the index tool with action=status."
CLI equivalent (no agent needed): tree-sitter-analyzer --codegraph-status
PyPI / uvx users — install skills: the
tsa-*skills are bundled in the wheel. Copy them once with:tree-sitter-analyzer --install-skills # into ./.claude/skills/ (this project) tree-sitter-analyzer --install-skills-global # into ~/.claude/skills/ (all projects)Git-clone users already have them under
.claude/skills/— no action needed.
# uv (required). This official convenience installer is mutable/not content-bound;
# see https://docs.astral.sh/uv/ for alternative manual installation methods.
curl -LsSf https://astral.sh/uv/install.sh | sh # macOS / Linux
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" # Windows
# Standalone install (persistent CLI command):
uv tool install "tree-sitter-analyzer[all,mcp]"
# — or skip installing entirely: the MCP entry below runs via uvx on demand.
# Inside a uv-managed Python project, use: uv add "tree-sitter-analyzer[all,mcp]"
See Supported Agents. Most clients want this MCP server entry:
{
"mcpServers": {
"tree-sitter-analyzer": {
"command": "uvx",
"args": ["--from", "tree-sitter-analyzer[mcp]", "tree-sitter-analyzer-mcp"],
"env": { "TREE_SITTER_PROJECT_ROOT": "/absolute/path/to/your/project" }
}
}
}
After restart: "Run the index tool with action=status."
CLI equivalent (no agent needed): tree-sitter-analyzer --codegraph-status
Check resolver behavior on your own repository — no install required:
uvx --from tree-sitter-analyzer miswire-audit .
It reports possible cross-language name collisions so you can inspect resolver behavior on your own repository. Results are diagnostic, not a competitive benchmark claim.
verdict: SAFE | CAUTION | UNSAFE | INFO | REVIEW | WARN | ERROR | NOT_FOUND, so orchestrators branch on outcomes without re-prompting.edit action=safe + edit action=guard + constraint DSL + edit action=impact + verdict envelopes — designed so agents know before they touch.An agent's cost is dominated by turns, not by the size of each reply: every extra tool call re-sends the whole conversation. TSA is built so that a question is answered by a call whose response already carries the evidence needed to stop asking.
TSA ships curated workflows under .claude/skills/tsa-*/:
tsa-landing, tsa-find, tsa-graph, tsa-structure, tsa-deps, tsa-index, tsa-health-watch, tsa-edit-safety, tsa-edit-then-verify, tsa-constraints, tsa-pr-review, tsa-refactor-queue, tsa-temporal.
Each skill ships an allowed-tools subset + procedure recipe + decision-surface schema, so the agent doesn't have to triage 8 tools on every question.
Highlights:
tree-sitter-analyzer --table full <file> # method/signature/complexity table
tree-sitter-analyzer --partial-read --start-line N --end-line M <file>
tree-sitter-analyzer --project-health # A-F grade across the project
# Note: --callers / --callees require the call-graph index — run --full-index first
tree-sitter-analyzer --full-index # build call-graph index (run once)
tree-sitter-analyzer --callers <symbol> # who-calls
tree-sitter-analyzer --codegraph-impact <fn> # blast radius + risk
tree-sitter-analyzer --affected <file...> # tests transitively affected
tree-sitter-analyzer --dead-code # transitive unreachable
tree-sitter-analyzer --check-constraints # architectural rules
tree-sitter-analyzer --safe-to-edit <file> # refuse if risky
tree-sitter-analyzer --uml class # Mermaid UML class diagram
TSA performs indexed code search and live source verification in process. No ripgrep or fd installation is required.
search-content and find-and-grep have been removed on develop. See the
migration guide and CLI codemap.
Public benchmark, performance, or competitive numbers are emitted only from the
provenance-bound registry in
benchmarks/codegraph_compare/claim_registry.json.
E4 evidence must bind exact tool names and versions, measurements, corpus,
benchmark date/version, and an artifact digest. Evidence below E4 remains
internal and cannot emit wording. See the benchmark runbook.
The absence of a generated item means that no quantitative public claim is currently authorized. Qualitative descriptions above are bounded product capabilities, not measured superiority claims.
Source code → tree-sitter parse → SQLite + FTS5 index (.ast-cache/index.db)
↓
nav (navigate) / structure (explore) / nav (callers) / ...
↓
JSON response envelope
(verdict + agent_summary + data)
↓
MCP client / CLI consumer
The 8 MCP tools expose indexed queries and direct source analysis.
Build the AST index explicitly before indexed symbol/context queries with
tree-sitter-analyzer --ast-cache --ast-cache-mode index --format json. Refresh
it after source changes with index action=sync. Indexed queries reuse cached
AST data; automatic warming is specific to individual tools.
claude mcp add tree-sitter-analyzer \
--env TREE_SITTER_PROJECT_ROOT="$PWD" \
-- uvx --from "tree-sitter-analyzer[mcp]" tree-sitter-analyzer-mcp
Verify: claude mcp list. The bundled tsa-* skills auto-discover from .claude/skills/.
PyPI / uvx users — install the bundled skills once with:
tree-sitter-analyzer --install-skills # into ./.claude/skills/ (this project)
tree-sitter-analyzer --install-skills-global # into ~/.claude/skills/ (all projects)
Git-clone users already have them — no action needed.
Edit claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\, Linux: ~/.config/Claude/):
{
"mcpServers": {
"tree-sitter-analyzer": {
"command": "uvx",
"args": ["--from", "tree-sitter-analyzer[mcp]", "tree-sitter-analyzer-mcp"],
"env": { "TREE_SITTER_PROJECT_ROOT": "/absolute/path/to/your/project" }
}
}
}
Create .vscode/mcp.json (note: servers, not mcpServers):
{
"servers": {
"tree-sitter-analyzer": {
"type": "stdio",
"command": "uvx",
"args": ["--from", "tree-sitter-analyzer[mcp]", "tree-sitter-analyzer-mcp"],
"env": { "TREE_SITTER_PROJECT_ROOT": "${workspaceFolder}" }
}
}
}
All read the same mcpServers schema as Claude Desktop. Cursor: Settings → MCP. Cline: MCP panel → Edit settings. Continue: ~/.continue/config.json under experimental.modelContextProtocolServers. Roo Code: MCP panel → Edit MCP Settings.
The repo ships a Dockerfile that builds the MCP server (stdio transport) from source, so the image always matches the committed code.
# Build once
docker build -t tree-sitter-analyzer-mcp .
# Run against the current repo (server speaks MCP over stdio; -i keeps stdin open)
docker run --rm -i --user "$(id -u):$(id -g)" \
-v "$PWD:/work" -w /work tree-sitter-analyzer-mcp
--user "$(id -u):$(id -g)" runs as your host UID/GID, so the .ast-cache/, decision journal, and any edit writes under the bind-mounted repo are owned by you, not root.
MCP client config (the project root inside the container is the mount point /work):
{
"mcpServers": {
"tree-sitter-analyzer": {
"command": "docker",
"args": [
"run", "--rm", "-i",
"--user", "1000:1000",
"-v", "/absolute/path/to/your/project:/work",
"-w", "/work",
"-e", "TREE_SITTER_PROJECT_ROOT=/work",
"tree-sitter-analyzer-mcp"
]
}
}
}
⚠️
TREE_SITTER_PROJECT_ROOTmust be absolute. The server enforces a security boundary against escapes viaSecurityValidator.
Generated from runtime registries; see docs/CODEMAPS/languages.md for the full capability matrix. 22 plugins: 13 pipeline-registered, 3 index-admitted, 0 call-dispatch-only, 5 data/markup, 1 scaffold. pipeline_registered is registration evidence, not positive cross-file binding proof.
pipeline_registered: C, C++, C#, Go, Java, JavaScript, Kotlin, PHP, Python, Ruby, Rust, Swift, TypeScript | index_admitted: Bash, Lua, Scala | call_dispatch_only: | data_markup: CSS, HTML, Markdown, SQL, YAML | scaffold: JSON
Mostly nothing. The defaults are designed so you can hook it into your agent and forget:
output_format: "json" parameter is retained for explicitness.TREE_SITTER_PROJECT_ROOT (env var, MCP) or --project-root (CLI).<project>/.ast-cache/. Safe to delete — auto-rebuilds.TREE_SITTER_OUTPUT_PATH for large-output write target.uv run pytest -q # bounded local quick gate
uv run pytest tests/ -q --timeout=120 -m "not e2e and not network and not benchmark" # comprehensive local suite
PYTEST_XDIST_AUTO_NUM_WORKERS=1 uv run pytest -q --maxfail=1 # quick gate, one worker (lower CPU load)
PYTEST_XDIST_AUTO_NUM_WORKERS=2 uv run pytest -q --maxfail=1 # quick gate, two workers (balanced)
uv run pytest --lf --maxfail=1 # rerun only failed tests from last run
uv run python check_quality.py --new-code-only # quality gate
git clone https://github.com/aimasteracc/tree-sitter-analyzer.git
cd tree-sitter-analyzer
uv sync --extra all --extra mcp
uv run pytest -q # quick gate (bounded)
See docs/CONTRIBUTING.md for the development guide.
Scope statements that would otherwise read as marketing. They are collected here so the install path above is not interrupted by them.
nav action=navigate inlines the body of every definition it matches and reports no truncation. A symbol name shared by classes in multiple files therefore returns the entire reference set in the same response. Use search action=symbol to disambiguate first, or nav action=callers / action=callees, which honor limit and set truncated.
symbol and function_name are both accepted by callers, callees, and impact. navigate and lineage require symbol; passing function_name to them raises instead of returning a verdict envelope.
Ordinary file analysis, index creation/update, and legacy index-backed queries are separate from certified snapshot access. Their existing Windows operational paths do not require the new private WAL snapshot kernel. They may create or update the cache; certified read-only access has a separate contract.
The snapshot implementation adds POSIX-only private database/WAL evidence capture, requiring
descriptor-relative operations, O_NOFOLLOW, a safe external temporary directory,
and successful source/manifest/projection checks. It does not deliver Windows
read-only snapshot parity or extend the existing qualification gate for explicit
access_mode="read_existing" consumers.
Windows snapshot certification was already unavailable in the develop baseline
(SECURE_FD_SNAPSHOT_UNSUPPORTED). It remains unavailable in this implementation
(WAL_PRIVATE_SNAPSHOT_UNSUPPORTED, completeness="unknown", no snapshot token).
This is not a statement that the physical index is empty or that ordinary queries
are disabled. Native Windows qualification for the new capture path has not been
performed; a local capability test is not a substitute for it.
The per-file certified_at state is not a replacement for full snapshot authority.
partial_at persistent history is not implemented or included in this PR.
An incomplete or unverifiable projection cannot authorize a certified consumer.
These subsystems back nav actions and the internal API; they are not part of the tool surface an agent configures. Their limits are stated rather than implied:
TQL temporal selectors compare modification timestamps, not modification counts.
The tql_schema action documents the window and the shared default for bare
:hot and :recently_modified. Depth queries retain exact definition identity
and fail explicitly when traversal limits are exceeded.
Pulse requests return snapshot-bound context. SQL reads for identity, relationships, reverse-import context and optional cached LSP enrichment share a savepoint without ending a caller-owned transaction. This is not a SQL round-trip or latency guarantee.
Pulse's Python reverse-import context uses the existing module resolver; this
is not a claim of complete cross-language module resolution. Comment context
requires an index rebuilt with comment extraction. Old indexes and languages
without comment extraction return COMMENTS_NOT_INDEXED, rather than an empty
success; explicitly omit comment context with the documented max_comments
setting when it is not needed. Missing legacy commit-message projections become
pending for lazy refresh; disabled activation is preserved. Legacy NULL
activation states also become pending, without clearing old messages or counts.
Enabled cached indexing cycles continue bounded activation refresh. Pulse exposes
unavailable activation as null, while temporal queries reject incomplete
activation evidence. Refresh reads real Git history through bounded batches;
failed message reads retain pending work rather than claiming completion.
Semantic queries require a known stored embedding model and a consistent dimension. Mixed or unknown models are errors, with no provider fallback. Offline tests use model doubles; they do not certify live-provider quality.
Pulse batches retain successful entries but report failure if a target fails. TQL treats missing or unreadable indexes as errors, distinct from a ready index with no matches. Public request validation rejects invalid types and limits before opening the index or invoking an embedding provider.
Cross-language-safe code-intelligence MCP for AI agents: 13 languages, family-gated call graph, blast radius, health grading, 8 facade tools, JSON envelopes, 100% local. Run miswire-audit on your repo
Resumen general
Cross-language-safe code-intelligence MCP for AI agents: 13 languages, family-gated call graph, blast radius, health grading, 8 facade tools, JSON envelopes, 100% local. Run miswire-audit on your repo.
Herramientas
Aún no hay lista de herramientas. Los servidores remotos la reciben tras la primera comprobación de estado.
Preguntas frecuentes
Copia en esta página la configuración stdio para Cursor, Claude Desktop, Claude Code o VS Code. Usa la instalación del publicador, no un proxy de PlugMCP.
Este registro no indica ninguna variable de entorno obligatoria.
Tree Sitter Analyzer se ejecuta localmente por stdio.
Última comprobación: 2026-11-12. Cross-language-safe code-intelligence MCP for AI agents: 13 languages, family-gated call graph, blast radius, health grading, 8 facade tools, JSON envelopes, 100% local. Run miswire-audit on your repo.
