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

Sonde

de anishmoncivargheseversión 0.4.4i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.anishmoncivarghese/sonde

Instalar

Resumen

Descripción del creador (original en inglés)

Local code graph for TypeScript, Python and Swift: who calls this, what breaks if I change it.

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

Necesitas

  • npmNode.js instalado (para el comando npx)

¿Qué app usas?

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

Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json

{
  "mcpServers": {
    "sonde": {
      "command": "npx",
      "args": [
        "-y",
        "@cheppulabs/sonde"
      ]
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add sonde -- npx -y @cheppulabs/sonde

Abrir en Cursor

O copia la configuración tú

Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json

{
  "mcpServers": {
    "sonde": {
      "command": "npx",
      "args": [
        "-y",
        "@cheppulabs/sonde"
      ]
    }
  }
}

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.

Abrir en VS Code

O copia la configuración tú

Pégalo en .vscode/mcp.json de tu proyecto

{
  "servers": {
    "sonde": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@cheppulabs/sonde"
      ]
    }
  }
}

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 10 nov 2026

  • ✓ Superada

    El creador coincide con el repo

    El nombre en el registro se verificó con la cuenta de GitHub anishmoncivarghese, 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 5620 servidores de esta categoría
  • Publicado en el registro más recientemente que el 33% de los otros 5620 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 5620 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 Sonde?

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 (0.4.4) llegó al registro hace 2 meses.

¿Qué apps pueden usarlo?

Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js 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:↓ Descargas por semanai★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi

GitHub

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

de githubMuy usado★ 34,2 milActualizado hace 7 días

Computadora o nube

Desktop Commander

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

de wonderwhy-erMuy usado↓ 709,6 mil/sem★ 10,2 milActualizado hace 19 días

Se ejecuta en tu computadora

Cloudflare MCP

Cloudflare MCP servers

de cloudflareMuy usado★ 4,4 milActualizado hace 14 meses

Se ejecuta en la nube✓ mcp.cloudflare.com

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.

Sonde

A local code-context engine for AI coding agents. Sonde indexes a TypeScript, Python, or Swift repository into a symbol-level graph in SQLite and exposes three MCP tools — find_symbols, query_graph, and get_impact_radius — so an agent can answer *who calls this*, *what breaks if I change it*, and *which tests relate to it* in one call instead of a search loop.

What the benchmark actually shows

The honest claim is not "finds what grep cannot". A competent agentic search loop finds the same structural evidence — we measured it, on a real 19,409-line repository, and it scored 1.000 recall on every task.

The claim is the same answers for a fraction of the cost, inside a budget:

On real production TypeScriptSondeAgentic search
Recall on structural tasks1.001.00
Tool calls1.08.0
Context tokens1,2623,621
Latency263 ms38,602 ms
Runs that blew the token budget0 of 63 of 6

Sonde matches the baseline's answers on every structural task while using ~3× less context, 8× fewer calls, and ~147× less wall-clock time — and it never exceeds the caller's token budget, because the packer truncates to it by construction. That is the trade being offered.

Where it loses. Behavioural queries with no shared vocabulary — *"where is the retry backoff decided?"* — score 0.00. Local semantic retrieval was built and measured and does not fix it (see the design doc §2.2); the capability is therefore not claimed. If your questions are mostly of that shape, an agentic search loop is the better tool today.

Numbers are reproducible: npm run bench:fixture && npm run bench:large. Full results in BENCHMARK-LARGE.md and BENCHMARK.md.

Install and run

npm install -g @cheppulabs/sonde

cd your-project sonde init

sonde init indexes the repository and registers sonde as an MCP server in this project's .mcp.json, asking before it writes anything (skip the prompt with sonde init --yes). It never touches an .mcp.json it can't safely merge into — an existing sonde entry that differs from what init would write is left alone and reported, not overwritten.

For Python repositories, use sonde init --resolve; the default tree-sitter tier did not pass the project's placement gate for structural queries.

Equivalent by hand, if you'd rather see every step:

sonde index .

then add to .mcp.json:

{ "mcpServers": { "sonde": { "command": "sonde", "args": ["mcp", "serve", "."] } } }

No account or hosted service is required.

Architecture documentation

sonde doc writes an ARCHITECTURE.md describing the repository's modules, how they depend on each other, and what each one exposes — generated from the graph, so it reports what the code actually does rather than what someone remembered.

sonde doc            # write ARCHITECTURE.md

sonde doc --stdout # print it instead sonde doc --check # fail if it is out of date (for CI) sonde doc --module src/store # symbol-level detail, never committed

It is meant to be committed and regenerated, not hand-edited. Regeneration is byte-identical when nothing changed, so it does not churn your diffs; when two branches both regenerate it, resolve the conflict by running sonde doc again rather than merging by hand. It refuses to overwrite an ARCHITECTURE.md it did not generate.

Three things it deliberately does not do:

  • It does not draw a dependency it cannot evidence. Module pairs that merely share symbol names are excluded and counted separately. On this repository two adapters share the filenames symbols.ts, parser.ts and references.ts, which manufactured 62 heuristic "references" between modules that never import each other — once the second-heaviest arrow in the diagram.
  • It does not pretend the diagram is complete. The diagram shows the heaviest dependencies and states how many it omitted; the table below it goes further, and --module has the rest. A diagram containing every dependency is unreadable and therefore shows nothing.
  • It does not claim to be current when it is not. The header names the commit it describes and warns when files have changed since.

What it guarantees

  • Never returns stale source bytes. Whenever a response includes source, Sonde re-reads and re-hashes the indexed byte range before returning it (spec §8.1, Guarantee A).
  • Always reports structural drift, rather than claiming completeness it cannot verify (spec §8.1, Guarantee B). sonde status shows the same drift and tier distribution carried by tool response envelopes.
  • Every edge is tier-labelled by how it was found — COMPILER (resolved exactly by a bundled type checker under --resolve: the TypeScript compiler for TypeScript, pyright for Python), LEXICAL (resolved through an import binding or lexical scope), HEURISTIC (member access or another relationship requiring type inference), EXTERNAL (target outside the indexed repository), or UNRESOLVED (genuinely unplaceable, with a reason).
  • Never fabricates an edge. An unresolved reference becomes EXTERNAL or UNRESOLVED — never a guessed target and never a silently dropped reference.

Accuracy

Sonde measures its zero-setup tree-sitter path against the TypeScript compiler on a pinned fixture and publishes the result, unflattering numbers included (spec §12). COMPILER edges use that compiler directly, so comparing them back to the same authority would not be an independent accuracy test.

Sonde edge accuracy vs the TypeScript compiler

Generated: 2026-08-23T18:16:41.557Z TypeScript: 5.9.3 (bundled; repository TypeScript is never loaded)

What these numbers cover. The oracle measures the tree-sitter resolution path — the zero-setup default, and the only tier whose accuracy is in question. COMPILER-tier edges come from the TypeScript compiler itself, so scoring them against the same compiler would measure nothing; they are exact by construction and excluded from these figures. Run sonde index --resolve to produce them.

The oracle is filtered to in-repo targets; node_modules and .d.ts declarations are excluded. Type-only references, JSX intrinsics, export =, decorators, and declaration merging are known expected divergences (spec §10). Tier rows compare that tier alone with the complete oracle, making each tier's independent contribution visible; ALL is the combined result.

Why precision below 1.000 is expected here

These divergences are structural, so reading a precision figure as "how often Sonde is wrong" overstates the error rate:

  1. Ambiguous member calls emit every candidate. For x.foo() with two visible foo declarations, Sonde emits both as confidence-weighted HEURISTIC edges. At most one matches the compiler, so the other counts as a false positive by construction. The alternative is guessing a single target, which invariant 1 forbids — a wrong resolved-looking edge is worse than two honestly heuristic ones. Precision is therefore capped below 1.000 wherever the fixture contains an ambiguous call.
  2. Constructor calls are ours alone. Sonde emits CALLS for new Foo(); the oracle does not model them, so each one is a false positive against ground truth that omits it.
  3. Member-level IMPLEMENTS is ours alone. Sonde derives an IMPLEMENTS edge from RegExpRouter.add to Router.add once the class declares it implements the interface. tsc reports heritage clauses at the type level only, so every member-level edge counts as a false positive against ground truth that does not model them. The capability is the reason impact on an interface method works at all, so the precision cost is disclosed rather than removed.

Counts are absolute, not percentages of a large corpus. Fixture edge totals appear below so a single edge's effect on each figure is visible.

tests/fixtures/repos/small

Fixture config SHA-256: e02e2d5003f96d1ad22519f04e10d687fe689cf9298e7fcbc588eab525dce1ad

Oracle edges: 9 · Sonde edges: 7 · one oracle edge moves recall by 11.1%

Edge kindTierPrecisionRecallTPFPFN
CALLSALL0.5001.000220
CALLSLEXICAL0.5000.500111
CALLSHEURISTIC0.5000.500111
IMPLEMENTSALL0.5001.000110
IMPLEMENTSLEXICAL0.5001.000110
IMPLEMENTSHEURISTIC1.0000.000001
INHERITSALL1.0001.000100
INHERITSLEXICAL1.0001.000100
INHERITSHEURISTIC1.0000.000001
REFERENCESALL0.5710.800431
REFERENCESLEXICAL0.8000.800411
REFERENCESHEURISTIC0.0000.000025

Overall: precision 0.571, recall 0.889

Regenerate with npm run bench:oracle.

CLI

sonde init [path] [--resolve] [--yes]      # index and register project MCP config

sonde index [path] [--resolve] # full index; optional compiler pass sonde update [path] [--resolve] # update; optional compiler pass sonde status [path] # freshness and tier distribution sonde search [path] # find_symbols sonde query [path] # query_graph sonde impact [path] --symbol # get_impact_radius by symbol sonde impact [path] --from-git-diff # impact from working-tree diff sonde doctor [path] # parser/database/tsc health sonde clean [path] # remove the cached index sonde mcp serve [path] # MCP server over stdio

impact also accepts repeatable --symbol options and --token-budget . The init, index, update, status, search, query, impact, doctor, and clean commands accept --json.

Known limitations

  • Node 22+ is required. better-sqlite3 needs it; installing on an older Node prints an EBADENGINE warning but still completes. If sonde then fails to run, this is why — upgrade Node rather than ignore the warning.
  • Python needs `--resolve`, and its edges are not oracle-verified. Without it, Python indexes at the tree-sitter tier only, which measured 62.81% unresolved on a real 56-file project and 57.39% on pydantic — far past the 30% ceiling this project requires, so it is not fit for structural queries. With --resolve, a bundled pyright drives a COMPILER tier and the same corpora measure 27.00% and 17.42% unresolved. That gate measured *placement* — whether a reference found a target — not whether the target was correct; TypeScript's edges are scored against tsc in ORACLE.md and Python has no equivalent oracle. On the worse corpus the margin is thin: 0.28 points once a known upward bias is reversed. See probes/python-placement/FINDINGS.md.
  • TypeScript, Python and Swift only; no other language adapter.
  • Swift resolution is heuristic, not compiler-backed, and one narrowing rule is unvalidated. References are narrowed by file visibility and explicit local type annotations, not full type inference. On a real 376-file Swift application this reached 74.84% placed / 25.16% unresolved — see probes/swift-narrowing/FINDINGS.md for the full measurement.

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

Pregunta a PopNx