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langflow-mcp-server

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create_memory_base

Creates a named memory base for a Langflow flow using a flow ID, supporting auto-capture, preprocessing, and embedding settings.

Instructions

Create a memory base for a flow (experimental, hidden in Langflow OpenAPI).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesMemory base name
flow_idYesAssociated flow ID
thresholdNoCapture threshold
auto_captureNoAutomatically capture memories
preproc_modelNoPreprocessing model name
preprocessingNoEnable preprocessing
embedding_modelNoEmbedding model name
embedding_providerNoEmbedding provider selected for the embedding model
preproc_kill_phraseNoPreprocessing kill phrase
preproc_instructionsNoPreprocessing instructions

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv4.12.2
    • addedInput schema / properties / embedding_provider
      Added value: +{
+  "description": "Embedding provider selected for the embedding model",
+  "type": "string"
+}
  2. First observedv4.11.0

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It discloses that the tool is experimental and hidden from the OpenAPI spec, which is genuinely useful, but says nothing about side effects, auth requirements, what a created memory base contains, or whether creation is reversible.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no waste. It is efficient but very thin, allocating its one clause to the experimental caveat rather than functional detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A 10-parameter mutation tool with no annotations and no output schema gets only a one-line description. Nothing covers permissions, defaults, or the outcome of creation, leaving substantial gaps for an agent to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all 10 parameters (name, flow_id, threshold, auto_capture, embedding settings, etc.) are already documented in the schema. The description adds no parameter meaning beyond that, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Create a memory base') and scopes it to a flow, which lets an agent distinguish it from list/get/update/delete_memory_base siblings. Sibling differentiation is implicit in the verb rather than explicit, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to create a memory base versus reusing an existing one, no prerequisites, and no named alternatives. The only contextual note is 'experimental, hidden in Langflow OpenAPI', which describes availability, not usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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