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Hashloom

de davet47versión 0.6.0i★ –iSe ejecuta en tu computadora
Nombre en el registroio.github.davet47/hashloom

Instalar

Resumen

Descripción del creador (original en inglés)

Content-addressed contracts and a verification cache that cut agent context by skipping proven code.

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: Otros

Instalación

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

Antes de instalar

Necesitas

  • PyPIuv de Python instalado (para el comando uvx)

¿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": {
    "hashloom": {
      "command": "uvx",
      "args": [
        "hashloom",
        "serve"
      ]
    }
  }
}

Ejecuta esto en tu terminal

claude mcp add hashloom -- uvx hashloom serve

Abrir en Cursor

O copia la configuración tú

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

{
  "mcpServers": {
    "hashloom": {
      "command": "uvx",
      "args": [
        "hashloom",
        "serve"
      ]
    }
  }
}

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": {
    "hashloom": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "hashloom",
        "serve"
      ]
    }
  }
}

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 davet47, 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 Otrosi

  • Más estrellas que el 0% de los otros 32484 servidores de esta categoría
  • Publicado en el registro más recientemente que el 32% de los otros 32484 servidores de esta categoría
  • Revisiones básicas iguales o mejores que el 100% de los otros 32484 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 Hashloom?

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 (0.6.0) 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 Python (uv) en tu computadora.

¿Qué puedo usar en su lugar?

En la misma categoría: Spec Driven Development, Remote Desktop Commander, Recta

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

Spec Driven Development

de formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Se ejecuta en tu computadora★ 440MITActualizado hace 14 meses
Instalar

Remote Desktop Commander

de desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Se ejecuta en la nube★ 211Actualizado ayer
Instalar

Recta

de RectaBuild

Cheaper cross-chain stablecoin routes for AI agents; 5 % of the verified saving, nothing if none.

Computadora o nubeActualizado hoy
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.

hashloom

Hashloom treats software units as content-addressed contracts rather than files. An MCP server that makes agent regeneration loops cheap.

Because contracts are content-addressed and dependency-aware, agents reuse verification, compute blast radius precisely, and regenerate code from a few hundred tokens of context instead of re-reading whole files. Build systems ask which files changed. Hashloom asks which software obligations changed.

The name is a coinage that says exactly what it is: a loom keyed by hashes. On a loom, the warp threads are the fixed, durable strands, and the shuttle weaves disposable weft through them. Contracts are warp. Code is weft. (Until 0.3.3 this project shipped as heddle-mcp; the engine is unchanged.)

The problem

Agents repeatedly pay to rediscover software structure. Spec-driven development tools made specs the durable artifact and code regenerable, but they run on plain files, so every regeneration loop re-derives what the project already knows:

  1. Context acquisition is expensive. Regenerating one unit means re-reading whole spec and source files: thousands of tokens to learn what a few hundred convey.
  2. Verification is uncached. Every regeneration re-runs (and re-reads the output of) the full relevant test surface, even for units whose contracts haven't changed.
  3. Blast radius is by convention, not mechanism. When a spec changes, nothing tells the agent precisely which dependents are invalidated.

The model

Hashloom treats each software unit as a content-addressed contract with explicit dependencies, not a file. A contract is a small YAML spec (signature, invariants, examples, dependency names); the implementation behind it is regenerable weft. Because every contract is hashed and its dependencies are named, the structure an agent keeps re-deriving from files becomes something hashloom computes once and serves.

Outcomes

The model buys three things, all mechanical:

  • Verification caching. A green test result is keyed on the contract, implementation, and dependency hashes, and served from cache until one of them changes. pytest runs only on a real miss.
  • Mechanical blast radius. A contract change reports the exact set of invalidated dependents, transitively and by hash, not by convention.
  • Tiny context packets. An agent regenerating a unit gets the contract, its dependencies' signatures, and its callers as one packet of a few hundred tokens, instead of the whole file closure.
The number

Same three regeneration tasks on a 20-contract sample project, once with raw file reads, once through hashloom (tiktoken cl100k, reproduce with uv run python bench/benchmark.py):

taskraw fileshashloomreduction
revenue_by_region1,9253695.2x
top_customers2,1373376.3x
revenue_by_category1,9423964.9x
total6,0041,1025.4x

Raw mode counts what a file-based agent reads per task: the unit's spec file, every transitive dep's spec file, every source module in the dep closure, the unit's test file, and the output of running the suite. It is deliberately generous to the baseline: it assumes the agent already knows the exact dependency closure, which is precisely the thing hashloom computes for you.

The same methodology sweeps *every* unit of all five example projects — Python, Go, TypeScript, Java, and C# — via bench/sweep.py, and works on any hashloom project including yours. Full sweeps average lower than the gate (they count the leaf types that barely benefit); the ratio tracks dependency depth, so deeper projects score higher. All the numbers, their distributions, and the honest caveats live in docs/benchmarks.md.

Quickstart

pip install hashloom

or from source: pip install "git+https://github.com/davet47/hashloom"

cd your-project hashloom init # creates .hashloom/ and contracts/ hashloom index # builds the store from contracts/

Point Claude Code at it:

claude mcp add hashloom -- hashloom serve

(Stdio transport; the server resolves the project by walking up from its working directory to the nearest .hashloom/.)

New to the workflow? docs/getting-started.md walks through building a package contract-first with an agent — the working rules to give it, the review loop, and the verify gate.

Contracts

One YAML file per unit in contracts/. Minimal, hand-writable, hashable:

name: revenue_by_region

signature: "(sales: list[Sale]) -> dict[Region, float]" deps: [Sale, Region] # other contract names invariants:

  • excludes sales where completed is false
  • excludes sales with null amount

examples:

  • in: "[Sale(region='QLD', amount=10, completed=True)]" out: "{'QLD': 10.0}"

tests: [tests/test_revenue.py::test_revenue_by_region] # pytest node IDs impl: src/revenue.py::revenue_by_region # current woven weft status: inferred # reverse-engineered, not yet human-reviewed; omit once confirmed

Subdirectories are namespaces: contracts/billing/invoice.yaml is the contract billing/invoice, so the same short name can live in different folders. A contract's name must match its path under contracts/.

When to write a contract

A contract belongs on a stable seam: an interface other units depend on and that you expect to outlive its current implementation. The implementation behind it is disposable weft, regenerated freely. Dropping a contract where it does not earn that place is correct use, not a failure. The failure mode is the opposite, over-pinning interiors you would happily rewrite, which turns the durable layer into busywork.

Contracts are reviewed artifacts. Authoring one is cheap and getting cheaper, so the real cost is reviewing it, not writing it. A wrong contract is worse than no contract, because the durable artifact now lies: agents will regenerate code to satisfy a spec that is itself incorrect. Review a contract the way you review an interface, not the way you skim generated code.

A contract an agent reverse-engineers from existing code can declare that it hasn't earned that review yet: status: inferred. Tools then flag — by default, never refuse — any blast-radius or verification answer that rests on it (inferred: true on dependents, an inferred list on verify results, a review queue in status). Teams that want unvetted contracts to hard-fail can opt in to strict provenance mode (.hashloom/config.json → {"strict_provenance": true}): verify then refuses such units with a structured inferred_contract error — no tests run, no verdict cached — until they're reviewed; reads and writes stay advisory so drafts can still land and be inspected. Absent means confirmed, and confirming an inferred contract after review is free: status is provenance, not meaning, so the flip invalidates nothing (under strict mode, a pre-existing green simply revives on confirm).

Hashing semantics
  • Contract hash: sha256 over a canonical form: keys sorted, whitespace normalised, comments stripped, example order preserved, dep order ignored. impl, tests, invariants, and status are excluded, so relocating files never invalidates, rewording an invariant is free, and confirming an inferred contract never invalidates anything. Invariants are documentation, not a machine obligation; the real check is the tests, whose source is in the verification key.
  • Impl hash: sha256 over the normalised AST of the implementation, so reformatting and comment edits never bust the cache. Docstrings are stripped too.
  • Verification key: (contract hash, impl hash, test-source hash, toolchain identity, transitive dep contract hashes). Hashloom caches verification results, keyed so that a change to any contract in the closure, to the implementation, to a test's own source, or to the toolchain identity forces a re-run. The identity is the toolchain version (python 3.11.7, go 1.21.5, node ts , java 21.0.3, dotnet 9.0.303) plus, when the project commits a dependency source at its root (uv.lock, go.sum, package-lock.json, pom.xml, ...), a deps = digest of it — so a green from an environment with a different declared dependency set is never trusted, and a 3.11 pass is never served to 3.13. The grain is the *committed declared* set (never OS/arch — CI greens still serve every platform); a venv that disagrees with its own lockfile is outside the key, which is one of the things shared-cache revocation exists for. Failures are never served from cache. For Python, the test-source hash covers each test's *fixture closure* too — the fixtures it requests (arguments, usefixtures, literal getfixturevalue), autouse fixtures in scope, and fixtures of fixtures, statically resolved through the test's module and conftest chain (nearest wins) — so editing only a conftest fixture busts exactly the tests that lean on it; fixture use the static walk cannot resolve degrades to hashing the whole chain, over-busting rather than under-busting. Two caveats. A cached pass assumes deterministic tests, so a green result that depended on wall-clock time, network, or randomness can outlive the condition that made it pass. And plain helper functions a test imports and calls (and non-Python test helpers) are still outside the hash — only the fixture graph is covered (see ISSUES.md).

MCP tools (the entire surface)

tooldoes
get_contractthe ~300-token context packet: contract + hash + one-line dep signatures + caller list
put_contractvalidate, write contracts/ .yaml, return new hash, a semantic diff of what changed, and every invalidated dependent
get_dependentsblast-radius query, direct or transitive, names + hashes; inferred (unreviewed) contracts flagged
verifyper-unit cached-pass / pass / fail plus a top-level ok gate bit; radius=true widens each name to its full blast radius; runs tests only on cache misses; failures come back as a ≤40-token assertion summary, never a traceback; inferred contracts in the closure flagged (refused under strict provenance mode)
statusdirty contracts, stale verifications, cache hit-rate, resolved verify interpreter, cumulative token counters

Every tool returns structured errors — {"error": {"code": "unknown_dep", "message": "'Regoin' not found — nearest: 'Region'"}} — never a stack trace.

The verify interpreter

verify runs your tests with the project's own python, resolved in order: hashloom serve --python PATH → .hashloom/config.json ({"python": "..."}) → an auto-detected /.venv → the interpreter running hashloom. So a globally-installed hashloom can verify a project against its own virtualenv without being installed into it; hashloom status shows which interpreter it resolved.

.hashloom/config.json also takes verify_timeout (seconds per pytest run, default 300) for suites that need longer than the default, pycache_trust (default true); set pycache_trust: false — or pass --no-pycache-trust — to clear the project's __pycache__ before each verify run, so a stale .pyc can never shadow the current source, and strict_provenance (default false) to make verify refuse units whose closure contains inferred contracts.

Beyond Python

The impl's file extension picks the language adapter — each

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

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