toolforte

Recall a value

memory_get

Read-onlyIdempotent

Read back a value you (or another session using the same API key) stored earlier with memory_set. Returns null when the key does not exist. Requires a free API key (Authorization: Bearer tf_...) so entries stay private to you: https://toolforte.com/developers

Input Schema

TableJSON Schema

Name	Required	Description	Default
`key`	Yes	The key to read

Output Schema

TableJSON Schema

Name	Required	Description
`key`	No	The memory key
`bytes`	No	Size in bytes
`value`	No	The stored value
`result`	No	The result, when it is not an object
`updatedAt`	No	When the entry was last written (ISO 8601)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedSep 5, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "bytes": {
+      "description": "Size in bytes",
+      "type": "number"
+    },
+    "key": {
+      "description": "The memory key",
+      "type": "string"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    },
+    "updatedAt": {
+      "description": "When the entry was last written (ISO 8601)",
+      "type": "string"
+    },
+    "value": {
+      "description": "The stored value",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

First observedSep 1, 2026

TDQS

A4.3/5.0

Behavior4/5

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

The annotations already cover read-only, idempotent, and non-destructive behavior. The description adds meaningful context beyond those: it returns null for nonexistent keys, requires an API key, and scopes entries to the same API key. This gives the agent a realistic model of cross-session behavior.

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

Conciseness5/5

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

Three short sentences, with the core purpose front-loaded, then the null-result behavior, then the authentication requirement. Every sentence earns its place; no redundant or vague wording.

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

Completeness5/5

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

The tool is a simple single-parameter read operation, and the description provides everything needed to invoke it correctly: what it reads, how to reference stored values, the not-found behavior, and the auth requirement. Since output schema exists, return value details beyond null do not need to be described.

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?

Input schema coverage is 100% and the key parameter is already documented as 'The key to read'. The description adds the memory_set linkage but no additional details about key format, naming conventions, or constraints beyond the schema, so it stays at the baseline for high schema coverage.

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

Purpose5/5

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

The description uses a specific verb-resource pair: 'Read back a value' stored with memory_set. It clearly distinguishes this from sibling write (memory_set), deletion (memory_delete), and listing (memory_list) tools, and specifies the null-return behavior for missing keys.

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

Usage Guidelines4/5

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

The description clearly indicates this tool is for retrieving a previously stored value, explicitly linking it to memory_set. It does not explicitly contrast with memory_list or memory_delete, so it lacks full when-not/exclusion guidance, but the usage context is clear and unambiguous.

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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TDQS

A3.8/5.0

Disambiguation5/5

Every tool targets a distinct resource or action, and the detailed descriptions clearly separate near neighbors like generate_test_bsn versus generate_brp_test_data, read_page versus url_screenshot versus url_to_pdf, and image_compress/convert/resize. Even with 40 tools, there is no real boundary-blurring overlap.

Naming Consistency3/5

All names are snake_case and readable, but the set mixes conventions: verb_noun (generate_*, validate_*), noun_verb (pdf_merge, image_resize), conversion-style names (csv_to_json, html_to_pdf), and bare nouns (base64, qr_code_png). The groups are recognizable, but there is no single predictable pattern.

Tool Count2/5

Forty tools is an oversized surface for an agent to consider on every call, well above the point where tool selection cost starts to hurt. The broad purpose explains the count, but many one-off utilities could be grouped or exposed selectively.

Completeness3/5

The server covers many domains—encoding, Dutch test data, image/PDF handling, memory, and workflows—but several categories are partial: there are no reverse conversions like json_to_csv or html_to_markdown, no PDF text extraction, and no workflow create/update/delete tools. Agents can work around some gaps, but notable operations are missing.

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