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PopNx MCPServidores MCP para quienes usan IA · explicados con palabras sencillas

AI Architect MCP Codebase

de cdeustversión 0.14.0i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.cdeust/ai-architect-mcp-codebase

Instalar

Resumen

Descripción del creador (original en inglés)

Codebase intelligence MCP — index any repo into a property graph; 26 tools for agents.

Los tres pilares de PopNx MCP

Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.

Qué puedes hacer con él

Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.

  • Conexión: Se ejecuta en tu computadora
  • Transporte: stdio
  • Categoría: Herramientas para desarrolladores

Instalación

Elige la app de IA que usas y copia la configuración.

Antes de instalar

¿Qué app usas?

Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.

Descargar el archivo .mcpb del creador

El enlace lleva al archivo del propio creador; no lo alojamos ni lo reempaquetamos. Abre el archivo y Claude Desktop lo instalará.

Ejecuta esto en tu terminal

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.

Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.

Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.

Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.

Qué puede hacer

Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.

Revisiones básicasi

Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub cdeust, dueña del repo

  • … Aún sin revisar

    Sigue en mantenimiento

    Todavía no hemos leído este repo en GitHub

  • … Aún sin revisar

    Tiene licencia

    Todavía no hemos leído este repo en GitHub

  • – No aplica

    El endpoint responde

    Este se ejecuta en tu computadora; no hay endpoint en internet

  • – No aplica

    Inicio de sesión con OAuth

    Se ejecuta en tu computadora y usa ajustes locales en su lugar

  • … Aún sin revisar

    Sin instrucciones ocultas en las descripciones de herramientas

    Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet

Comparado con otros en Herramientas para desarrolladoresi

  • Más estrellas que el 0% de los otros 1385 servidores de esta categoría
  • Publicado en el registro más recientemente que el 58% de los otros 1385 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 1385 servidores de esta categoría

Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.

Preguntas frecuentes

¿Es seguro AI Architect MCP Codebase?

Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.

¿Qué claves o códigos necesita?

El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.

¿Se ejecuta en mi computadora o en la nube?

Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).

¿Sigue en mantenimiento?

El repo de GitHub cambió por última vez –, y la última versión (0.14.0) llegó al registro hace 40 días.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas MCPB en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: GitHub, Desktop Commander, Cloudflare MCP

Alternativas

Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.

Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

GitHub

de github

Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.

Computadora o nube★ 34.245MITActualizado hace 3 días
Instalar

Desktop Commander

de wonderwhy-er

MCP server for terminal commands, file operations, and process management

Se ejecuta en tu computadora★ 10.225MITActualizado hace 15 días
Instalar

Cloudflare MCP

de cloudflare

Cloudflare MCP servers

Se ejecuta en la nube★ 4446Apache-2.0Actualizado hace 14 meses
Instalar

README del creador

Abrir el README

Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.

An MCP server that indexes a repository into a local code graph and answers structural questions about it: who calls this, what depends on it, what a diff touches, how execution reaches a function.

What it is · Install · First session · Tools · Limits · Development


What it is

ai-architect-mcp-codebase parses a repository with tree-sitter, stores the symbols and their relationships (definitions, calls, imports, implementations, uses) in an embedded LadybugDB graph database on your machine, and exposes that graph to an agent through MCP tools. An agent can search the graph, look up a symbol with its callers and callees, list the reverse dependencies of a symbol, follow execution flows from entry points, map a git diff onto the symbols it changes, and compare two graphs of the same code. Answers about symbols carry source locations and the limits of the analysis behind them.

The server does not edit the files it indexes. It writes its graph and sidecar files under the output_dir you pass, plus a snapshot in the repository only when you ask for the team-shared artifact. Indexing and queries run locally without network calls, no language model reads the code, and nothing is uploaded. The graph is a directory you own.

The graph comes from static parsing of source text, so some things stay out of it. A call made through reflection, dynamic dispatch, generated code, or a macro the parser does not expand has no edge unless an optional language-server pass (lsp: true) or runtime traces (ingest_traces) supply one. Method calls through a receiver are resolved statically only for the receiver shapes listed below; the rest need the language-server pass. Ruby gets a shallow extraction with no imports or visibility. Process flows are reachability in the graph from declared entry points, capped at depth 20, with no observation of execution. An empty answer can mean "no such relationship" or "not indexed", and the coverage report exists to tell those apart.

Install and register

Claude Code plugin
claude plugin marketplace add cdeust/ai-architect-mcp-codebase

claude plugin install ai-architect-mcp-codebase@ai-architect-mcp-codebase-marketplace

The plugin downloads the release binary and verifies its Sigstore provenance before running it; this needs GitHub CLI 2.68 or newer. The plugin starts the full profile unless AP_PROFILE=core is set.

Other MCP hosts
cargo install ai-architect-mcp-codebase

ai-architect-mcp-codebase install # writes the MCP entry for each detected host

install detects Claude Code, Codex CLI, Gemini CLI, Cursor, VS Code and Zed, adds only its own entry to each config file, and never overwrites a file it cannot parse. --dry-run previews the changes; uninstall removes them. To configure a host by hand, register the binary as a stdio server:

{

"mcpServers": { "ai-architect": { "command": "ai-architect-mcp-codebase", "args": ["--profile", "core"] } } }

docs/install.md has the per-host snippets (Codex, Gemini, Cursor, Windsurf, VS Code, the OpenAI Agents SDK), the optional Grep/Glob hook, the plugin's release verification, and the developer escape hatch for running a local build inside the plugin.

Build from source
git clone https://github.com/cdeust/ai-architect-mcp-codebase.git

cd ai-architect-mcp-codebase cargo build --release # about five minutes the first time (LadybugDB's C++ core)

Rust 1.95.0 is pinned by rust-toolchain.toml, and CMake is required.

Tool profiles

The server registers one of two tool sets, chosen at startup with --profile or the AP_PROFILE environment variable (the flag wins).

ProfileToolsUse
core8: health_check, analyze_codebase, search_codebase, get_context, get_symbol, get_impact, query_graph, detect_changesRecommended for agents. Analyze once, then search, inspect and measure impact.
fullall 27Adds the manual graph passes, history, runtime traces, the verification tools, the artifact builder and the finding-record tools.
ai-architect-mcp-codebase --profile core   # the 8 core tools

AP_PROFILE=core ai-architect-mcp-codebase # same, through the environment ai-architect-mcp-codebase # default: full (all 27)

The default stays full until the next major version, because shrinking the default tool surface is a breaking change. New agent setups should use the core profile (8 read-only tools): analyze_codebase already runs index, resolve and cluster in one call, and leaving out the 19 hidden tools keeps the tool prompt small.

A first session

health_check()

→ server name and version, protocol version, registered tool count

analyze_codebase(path: "/path/to/repo", output_dir: "/tmp/repo-graph") → index, resolve, cluster and build the search index in one call → node and edge counts, communities, processes, and the coverage report

search_codebase(graph_path: "/tmp/repo-graph/graph", query: "tool request dispatch") → ranked symbols (BM25 and sparse TF-IDF fused with RRF), paged with next_offset

get_context(graph_path, qualified_name: "src/main.rs::handle_tool_call") → the symbol with its callers, callees, imports, implementations, community and processes; suggestions when the name does not match exactly

get_impact(graph_path, qualified_name: "src/main.rs::handle_tool_call") → callers, importers, users and implementors, the communities and processes affected, and an epistemic label (exact or lower-bound) with its reasons

detect_changes(graph_path, codebase_path: "/path/to/repo", base_ref: "main", head_ref: "HEAD") → symbols the diff adds, modifies or deletes, with a heuristic risk score each

query_graph(graph_path, graph: "missed") → the files the index could not fully cover, to check with grep

Re-run analyze_codebase after edits; indexing is incremental by default.

27 MCP Tools

Each tool takes JSON arguments checked against its JSON Schema and returns structured JSON, with a named reason code on error. No tool calls a language model. Agent installs rarely need all 27; the core profile registers just the 8 code-intelligence tools.

Server:                  health_check

Index and resolve: analyze_codebase · index_codebase · resolve_graph · lsp_resolve · cluster_graph · ingest_traces Coverage: index_status Search and context: search_codebase · get_symbol · get_context · query_graph Impact and processes: get_impact · get_processes · detect_changes History: index_history Verification: check_security_gates · verify_semantic_diff · validate_prd_against_graph · check_doc_claims Artifact export: prepare_prd_input Finding records: extract_finding · refine_finding · start_verification · append_clarification · finalize_verification · abort_verification

ToolCoreWhat it does
health_checkyesReturns server name and version, MCP protocol version and the registered tool count, which shows the active profile.
analyze_codebaseyesRuns index, resolve and cluster in one call and builds the search index; lsp: true adds the language-server pass. Returns statistics and the coverage report.
index_codebaseWalks and parses the repository into /graph/. Incremental by default; can export or import the team-shared graph artifact.
resolve_graphAdds cross-file Imports, Calls, Implements, Extends and Uses edges with confidence scores.
lsp_resolveResolves remaining calls through rust-analyzer, pyright or typescript-language-server.
cluster_graphDetects communities (Louvain with C2 repair) and traces processes from entry points.
ingest_tracesFolds runtime caller-to-callee observations (OTel spans, profiler or coverage traces) into the graph, and adds OBSERVED_CALLS edges where static resolution found none.
index_statusNode and edge counts plus the coverage report.
search_codebaseyesHybrid ranked search over symbols, and BM25 search over documentation files.
get_symbolyesExact lookup by qualified name with every incoming and outgoing edge; sibling_graphs looks for a definition in other repositories' graphs.
get_contextyesOne symbol with its relationships grouped by kind, its community and its processes.
query_graphyesRead-only Cypher, paged; graph: "missed" lists what the index did not cover.
get_impactyesReverse dependencies of a symbol or file, with affected communities and processes and an epistemic label.
get_processesLists execution flows with entry point, entry kind (main, test, proof, handler, lib_entry), depth and size.
detect_changesyesMaps a unified diff, or base_ref..head_ref, onto the symbols, communities and processes it touches.
index_historyAdds git history as Commit and Version nodes linked to the files and symbols each commit changed.
check_security_gatesChecks a list of changed symbols for auth-community touch, public-API change, unresolved imports and test-coverage gaps.
verify_semantic_diffCompares a before graph and an after graph: added and removed nodes and edges, dangling references, new unresolved imports, new cycles (Tarjan SCC), and a heuristic regression score.
validate_prd_against_graphChecks a product requirements document against the graph: symbols it names that do not exist, changes that span several communities, and "does not affect X" claims contradicted by process membership.
check_doc_claimsChecks what a document claims about the code, one claim at a time, each anchored to the exact text at a file:line: symbols, files and modules that exist, items declared pub, test and proof counts, enum variant counts. Every row is supported, contradicted, not found, not verifiable (with the reason) or rejected for a bad anchor, with a replayable query as evidence. An absence, or a count the graph holds only as a lower bound, is never called contradicted.
prepare_prd_inputWrites a JSON bundle of graph facts (matched symbols, affected communities and processes, graph statistics) for a finding or a free-text feature description.
extract_finding, refine_findingNormalize an incoming finding to a canonical JSON record and store an agent's refinement of it.

| start_verification, append_clarification, finalize_verification, abort_verification | | Record a ques

Solo se muestra el principio; lee el resto en el repo

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