Valem

Installation

Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.

5/5 Prüfungen bestanden · Was du fragst, läuft über den Server des Anbieters (valem.run)

claude mcp add --transport http --scope user valem https://valem.run/mcp

{
  "mcpServers": {
    "valem": {
      "url": "https://valem.run/mcp"
    }
  }
}

{
  "servers": {
    "valem": {
      "type": "http",
      "url": "https://valem.run/mcp"
    }
  }
}

Welche Apps ihn nutzen können

Basierend darauf, wie sich dieser Server verbindet, und auf der eigenen Doku jeder App, geprüft am 10. Nov. 2026.

Verbinden sich über das Internet in

ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast

Alle Apps, mit Vor- und Nachteilen →

Was er kann

Tool-Namen und -Beschreibungen genau so, wie der Server sie am 10. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.

• list_models

  List the ids of all currently registered Valem models (alphabetical).

• create_model

  Create a new model from a declarative ModelSpec. The spec carries the JSON schema plus derivations (computed fields), constraints (invariants), and optional effects. Returns the created id. Fails (isError) on an invalid spec. If the requested id is already taken, a numeric postfi

• get_model_info

  Get summary info for a model: id, version, and derivation/meta/constraint/effect counts.

• get_spec

  Get the full stored ModelSpec JSON for a model.

• get_library

  List the JSONata functions and values a model's library exports — what an expression in this model may call, with signature, arity and originating layer. Call it before writing an expression so you reuse the model's existing vocabulary instead of re-deriving it. Returns null when

• get_state

  Get a model's merged state (base fields plus all computed derived fields). On a large model this is the biggest context cost — narrow it: pass 'paths' to project only specific subtrees (canonical addresses, each spliced back into a pruned document at its address), and/or 'depth'

• get_field

  Get the value of a single field by its JSON Path address (e.g. "$.order.total"). Evaluates a LAZY derivation on demand.

• mutate

  Apply field mutations to a model and run the reactive pipeline (derivations recompute, constraints enforce, effects dispatch). 'mutations' is a flat map keyed by canonical JSON Path address, e.g. {"$.order.qty": 3}. A ROLLBACK constraint violation returns isError with the structu

• patch_model

  Apply an RFC 6902 JSON Patch document to a model and run the reactive pipeline. Unlike 'mutate' (a flat address→value map), a patch expresses array insert/remove/move and test/copy ops, e.g. [{"op":"add","path":"/order/items/-","value":{...}}, {"op":"remove","path":"/order/items/

• get_effective_schema

  Get the effective JSON Schema for a field: the static schema overlaid with LIVE meta-derived constraints (current min/max/required/…). Check this BEFORE writing a value to learn what the reactive pipeline will accept, instead of discovering an invalid mutation only by trying it a

• snapshot

  Capture an immutable point-in-time snapshot of a model's state (base document + derived/meta caches). A natural safety step before a risky evolve_spec: keep the returned snapshot and, if the change goes wrong, hand it back to 'restore' to roll the state back.

• restore

  Restore a model's state from a snapshot previously returned by 'snapshot' (pass it back verbatim as 'snapshot'). Overwrites the model's current base state. The snapshot must be for the same model.

• explain

  Explain why a field is what it is: returns the recent derivation/constraint trace records for a path from the in-memory ring buffer (inputs, expression, result). For a constraint use the synthetic path "$constraint: ". Trace records can be bulky — pass 'limit' to return only the

• get_history

  List the ISO-8601 timestamps of a model's committed mutations (most recent 100).

• get_audit

  Query a model's durable, append-only audit trail (newest-first): one record per committed reactive cycle (mutations, derivedUpdated, traces, flaggedConstraints, dispatchedEffects, source, sequence). This is the queryable superset of get_history/explain — it survives the in-memory

• verify_audit

  Verify the tamper-evidence hash chain of a model's durable audit trail. Returns {valid, recordsChecked, firstBrokenSequence, detail}; a false 'valid' points at the first altered/reordered/deleted record. (Embedded mode has no hash chain and reports valid.)

• upload_blob

  Store binary content (base64-encoded in 'data') in the content-addressed blob store and get back a BlobRef {$blobId, $mediaType, $bytes} to embed in a model's binary field. Storage is content-addressed (SHA-256), so uploading identical bytes returns the same $blobId.

• download_blob

  Fetch a blob's bytes by id, base64-encoded in the result. Pass 'modelId' to fetch a blob referenced by a specific model (access-scoped); omit it for a direct store fetch. Large blobs may exceed the result-size limit — this channel suits small binaries only.

• evolve_spec

  Apply an incremental SpecEvolution diff to a model, preserving live state. Returns the new version. Fails (isError) if the evolved spec is invalid, if expectedVersion no longer matches, or if a schema change would strand existing state. Prefer targeted diffs (upsertSchemaNodes/up

• delete_model

  Remove a model from the registry. Fails (isError) if the model does not exist.

• get_view

  Evaluate a model's embedded view definition against current state and return the resolved component tree. Pass an optional 'viewId' for a named view; omit for the default view.

• get_domain_guidance

  Get vetted instructions for the hard modelling shapes this domain involves (progressive tax/fee charges, per-period schedules, classification, date math, group-by, …). Read the model description in ANY language, pick the matching topic ids, and call this BEFORE authoring the spec

• validate_spec

  Validate a ModelSpec WITHOUT creating it: returns a 'valid' flag plus structured findings (errors + warnings, each with a location and message). Use this to iterate on a draft — fix the reported errors, re-validate — before committing with create_model.

• eval_expression

  Evaluate a single JSONata expression against a sample input document and return the computed value, or the exact compile/eval error. Write the expr exactly as in a derivation/constraint 'expr': bare dot-paths, no leading $ (e.g. "loan.amount * loan.annualRate / 1200"). Use this t

• test_spec

  Run a spec's embedded test cases (or ad-hoc given->expect cases) through the real reactive pipeline in a throwaway runtime, returning pass/fail plus per-field failures (path, expected, actual). Use this to certify domain behavior before create_model / promotion.

• dry_run

  Compile a candidate ModelSpec in an ISOLATED throwaway runtime, apply optional sample mutations, and return the resulting merged state (base + derived) — WITHOUT registering it in the live registry. Use this to preview the full reactive cascade of a draft spec.

• convert_spreadsheet

  Compile an uploaded .xlsx workbook's OWN formulas into a ready ModelSpec — deterministic transpilation (Excel formula language -> JSONata), never an LLM call: every number the compiled spec computes is checked to exactly match what the source workbook itself computed. One workshe

• search_document

  Deterministic, LLM-free search over an uploaded PDF/DOCX: ranks the document's pages/sections against your query (term-overlap, no embedding model, no network call) and returns the top matches with page/section citations and verbatim quotes. Cost is bounded by topK, never by docu

• pair_browser

  Pair this MCP session with a browser tab on the hosted Valem sandbox so both drive the same live model session. Mints a pairing on first call (or resumes an existing not-yet-approved one) and waits up to a minute for the developer to approve it. Returns {status:"paired"|"already_

• valem_spec_guide

  How to write a Valem ModelSpec that render_model accepts: sections, path notation, JSONata rules, view components and common mistakes. Call this once before writing your first spec in a conversation.

• render_model

  Show the user a Valem model as an interactive card they can edit in the chat: a form whose computed fields update on every change, checked by a deterministic engine. Use it when the user asks for a calculator, quote, budget, planner, pricing or any model with inputs and computed

• explain_value

  Explain how a value in a Valem card was computed: the formula, the values it read and the inputs it ultimately comes from, as Valem's engine has them for the given inputs. Use it when the user asks why a number is what it is. Pass the specHash and current inputs from the latest r

• valem_recompute

  Called by the Valem card when the user edits an input. Not for direct use: call render_model instead.

• show_model

  Show the user one of this server's models (created with create_model) as an interactive card in the chat. Every edit the user makes in the card is a mutate on the model, so get_state and explain see it. Use it after create_model or evolve_spec when the user should see or try the

• valem_card_edit

  Called by the Valem card when the user edits a stored model. Not for direct use: call mutate instead.

Basischecksi

Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 12. Nov. 2026

• ✓ Bestanden

  Entwickler passt zum Repo

  Der Registry-Name wurde mit dem GitHub-Konto vlad-public-code bestätigt, dem das Repo gehört

• ✓ Bestanden

  Wird noch gepflegt

  Code zuletzt geändert: vor 10 Tagen

• ✓ Bestanden

  Hat eine Lizenz

  Nutzt Apache-2.0

• ✓ Bestanden

  Endpunkt antwortet

  Antwort in 178 ms (HTTP 200)

• – Nicht zutreffend

  Anmeldung mit OAuth

  Keine Anmeldung nötig

• ✓ Bestanden

  Keine versteckten Anweisungen in Tool-Beschreibungen

  Wir haben 35 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden

Nutzerbewertungen

Noch keine Bewertungen

Mit Google anmelden, um zu bewerten

Im Vergleich mit anderen in Dokumente, Tabellen & Büroarbeiti

• Mehr Sterne als 0 % der anderen 3809 Server in dieser Kategorie
• Neuer in der Registry veröffentlicht als 25 % der anderen 3809 Server in dieser Kategorie
• Basischecks gleich gut wie oder besser als bei 100 % der anderen 3809 Server in dieser Kategorie

Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.

Andere in derselben Kategorie

Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.

So liest du eine Karte:↓ Downloads pro Wochei★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti

Puter MCP

Puter MCP enables AI tools to interact with Puter: manage files, websites, workers, and more

von HeyPuter·Weit verbreitet·★ 44.148·Aktualisiert vor 5 Monaten

Läuft in der Cloud✓ vom Dienst · puter.com

Installieren

XcodeBuildMCP

XcodeBuildMCP provides tools for Xcode project management, simulator management, and app utilities.

von getsentry·Weit verbreitet·↓ 130.486/Wo. geteiltes Paket·★ 6563·Aktualisiert vor 4 Monaten

Läuft auf deinem Computer✓ vom Dienst · xcodebuildmcp.com

Installieren

XcodeBuildMCP

XcodeBuildMCP provides tools for Xcode project management, simulator management, and app utilities.

von cameroncooke·Weit verbreitet·↓ 130.486/Wo. geteiltes Paket·★ 6563·Aktualisiert vor 14 Monaten

Läuft auf deinem Computer

Installieren

README vom Entwickler

# Claude Code

docker run --rm -p 8080:8080 ghcr.io/vlad-public-code/valem:latest

{

# Build the fat jar (first time)

// stdin

# From the repo root — build and start the Spring Boot server on port 8080.

# Anthropic (default provider)

cd valem-ui

# Create a model

# All modules

cd valem-e2e