Index / MCP servers / Valem

Valem MCP server

Valem is a remote MCP server that gives an AI agent 27 tools, among them create_model, delete_model, download_blob. It answers at https://valem.run/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 6 of 6 times since 11 September 2026; the last check, on 24 October 2026, succeeded.

Status
Answering
Tools
27
Reliability
6 of 6 checks
Response time
162 ms
Transport
streamable HTTP
Last checked
24 October 2026

Valem - Deterministic reactive state models. Create your own calculators/forms with AI

Description as the publisher wrote it.

The 27 tools Valem offers

ToolWhat it does
create_modelCreate 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 request
Inputs: spec
delete_modelRemove a model from the registry. Fails (isError) if the model does not exist.
Inputs: id
download_blobFetch 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 sma
Inputs: blobId, modelId
dry_runCompile 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 cas
Inputs: spec, mutations
eval_expressionEvaluate 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.amoun
Inputs: expr, input, library, constants
evolve_specApply 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. Pre
Inputs: id, evolution
explainExplain 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 "$constraint:<id>". Trace records can
Inputs: id, path, limit
get_auditQuery a model's durable, append-only audit trail (newest-first): one record per committed reactive cycle (mutations, derivedUpdated, traces, flaggedConstraints, dispatchedEffects, source, sequence). This is the queryable superset of get_his
Inputs: id, pathPrefix, from, to, limit
get_domain_guidanceGet vetted instructions for the hard modelling shapes this domain involves (progressive tax/fee charges, per-period schedules, classification, date math, group-by, …). Read the model description in ANY language, pick the matching topic ids,
Inputs: topics
get_effective_schemaGet the effective JSON Schema for a field: the static schema overlaid with LIVE meta-derived constraints (current min/max/required/…). Check this BEFORE writing a value to learn what the reactive pipeline will accept, instead of discovering
Inputs: id, path
get_fieldGet the value of a single field by its JSON Path address (e.g. "$.order.total"). Evaluates a LAZY derivation on demand.
Inputs: id, path
get_historyList the ISO-8601 timestamps of a model's committed mutations (most recent 100).
Inputs: id
get_libraryList 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 inst
Inputs: id
get_model_infoGet summary info for a model: id, version, and derivation/meta/constraint/effect counts.
Inputs: id
get_specGet the full stored ModelSpec JSON for a model.
Inputs: id
get_stateGet 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 d
Inputs: id, at, paths, depth
get_viewEvaluate 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.
Inputs: id, viewId
list_modelsList the ids of all currently registered Valem models (alphabetical).
mutateApply 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. {"$.order.qty": 3}. A ROLLBACK constraint vi
Inputs: id, mutations, includeTraces
pair_browserPair this MCP session with a browser tab on the hosted Valem sandbox so both drive the same live model session. Mints a pairing on first call (or resumes an existing not-yet-approved one) and waits up to a minute for the developer to approv
patch_modelApply an RFC 6902 JSON Patch document to a model and run the reactive pipeline. Unlike 'mutate' (a flat address→value map), a patch expresses array insert/remove/move and test/copy ops, e.g. [{"op":"add","path":"/order/items/-","value":{...
Inputs: id, patch, includeTraces
restoreRestore a model's state from a snapshot previously returned by 'snapshot' (pass it back verbatim as 'snapshot'). Overwrites the model's current base state. The snapshot must be for the same model.
Inputs: id, snapshot
snapshotCapture an immutable point-in-time snapshot of a model's state (base document + derived/meta caches). A natural safety step before a risky evolve_spec: keep the returned snapshot and, if the change goes wrong, hand it back to 'restore' to r
Inputs: id
test_specRun a spec's embedded test cases (or ad-hoc given->expect cases) through the real reactive pipeline in a throwaway runtime, returning pass/fail plus per-field failures (path, expected, actual). Use this to certify domain behavior before cre
Inputs: spec, tests
upload_blobStore binary content (base64-encoded in 'data') in the content-addressed blob store and get back a BlobRef {$blobId, $mediaType, $bytes} to embed in a model's binary field. Storage is content-addressed (SHA-256), so uploading identical byte
Inputs: data, mediaType
validate_specValidate 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
Inputs: spec
verify_auditVerify 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
Inputs: id

Add Valem to your AI client

Every block below points at https://valem.run/mcp. Pick your client and copy.

Claude Code: one command in your terminal
claude mcp add --transport http valem https://valem.run/mcp
Claude Desktop: claude_desktop_config.json
{
  "mcpServers": {
    "valem": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://valem.run/mcp"]
    }
  }
}
Cursor: ~/.cursor/mcp.json, or .cursor/mcp.json in a project
{
  "mcpServers": {
    "valem": {
      "url": "https://valem.run/mcp"
    }
  }
}
VS Code and GitHub Copilot: .vscode/mcp.json
{
  "servers": {
    "valem": {
      "type": "http",
      "url": "https://valem.run/mcp"
    }
  }
}
Zed: Zed settings.json
{
  "context_servers": {
    "valem": {
      "url": "https://valem.run/mcp"
    }
  }
}
Windsurf: ~/.codeium/mcp_config.json
{
  "mcpServers": {
    "valem": {
      "serverUrl": "https://valem.run/mcp"
    }
  }
}
JetBrains AI Assistant: Settings, Tools, AI Assistant, MCP, New MCP Server, as JSON
{
  "mcpServers": {
    "valem": {
      "url": "https://valem.run/mcp"
    }
  }
}
Continue: .continue/mcpServers/neuronto.yaml
name: Valem
version: 0.0.1
schema: v1
mcpServers:
  - name: Valem
    type: streamable-http
    url: https://valem.run/mcp
Gemini CLI: ~/.gemini/settings.json
{
  "mcpServers": {
    "valem": {
      "httpUrl": "https://valem.run/mcp"
    }
  }
}
Codex CLI: MCP server config
{
  "mcpServers": {
    "valem": {
      "type": "http",
      "url": "https://valem.run/mcp"
    }
  }
}
Warp: MCP servers, + Add, paste JSON
{
  "mcpServers": {
    "valem": {
      "url": "https://valem.run/mcp"
    }
  }
}
Goose: a one-click extension link
goose://extension?url=https%3A%2F%2Fvalem.run%2Fmcp&type=streamable_http&id=valem&name=Valem

Is Valem up right now?

It answered our last check on 24 October 2026 in 162 ms. Over 6 checks since 11 September 2026 it answered 6. Status here comes from Neuronto's own probes, not from the publisher.

MCP servers similar to Valem

Questions about Valem

How many tools does Valem have?

27, as returned by the server's own tools/list on 22 September 2026: create_model, delete_model, download_blob, dry_run, eval_expression, evolve_spec, explain, get_audit, and 19 more.

Is Valem down?

It answered our last check on 24 October 2026 in 162 ms. Over 6 checks since 11 September 2026 it answered 6.

How do I add Valem to Cursor?

Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://valem.run/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.

Does Valem need an API key?

It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.

Where this comes from

Publisher: io.github.vlad-public-code. Endpoint host: valem.run. ARD identifier: urn:air:io.github.vlad-public-code:mcp:valem. First indexed 10 September 2026. The tools are exactly what the server returned; nothing on this page is inferred from its name. Ranking in Neuronto search is never for sale.

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