Overview
Perfect for computer science education, digital logic design, and verifying boolean expressions with automatic operator normalization.
Live Test Truth Table Generation for AI Agents Source →
The tool
Once your client is connected to the VerveContext server, this appears in its tool list as TruthTableGenerationforAIAgents. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.
{
"name": "TruthTableGenerationforAIAgents",
"arguments": {
"expression": "A AND B OR C"
}
}You do not name the tool yourself; the model picks it. Asking about A AND B OR C in the terms this source covers is enough for it to reach for TruthTableGenerationforAIAgents on its own — naming it explicitly also works, and is the way to force the call.
Connecting
One server URL covers every source in the catalog, including this one. Authorization is OAuth: the client opens a browser once, and there is no key to paste into a config file.
{
"mcpServers": {
"vervecontext": {
"url": "https://api.vervecontext.com/v1/mcp"
}
}
}https://api.vervecontext.com/v1/mcpPer-client setup — Claude, Cursor, VS Code, ChatGPT — is on the MCP setup page.
Arguments
These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made. Premium arguments are accepted on every plan but only take effect on plans that include them.
| Argument | Type | Description |
|---|---|---|
expressionRequired | string | Boolean expression using A-Z variables and operators (AND, OR, NOT, XOR, NAND, NOR) |
What the model gets back
The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.
{
"status": "ok",
"error": null,
"data": {
"expression": "A AND B OR C",
"normalized": "A && B || C",
"variables": [
"A",
"B",
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"O",
"R"
],
"variableCount": 7,
"rowCount": 128,
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}
Response fields
Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.
| Field | Type | Example | Description |
|---|---|---|---|
expression | string | A AND B OR C | Original boolean expression input by user |
normalizedPremium | string | A && B || C | Expression normalized with standard operators like && and || |
variablesPremium | array | ["A","B","C"] | Array of unique variable names found in expression |
variableCountPremium | number | 7 | Total count of unique variables in boolean expression |
rowCountPremium | number | 128 | Number of rows in truth table (2^variableCount) |
rows | array[128] | Array of truth table rows with inputs and result values | |
rows.0.inputs | object | {…} | Input variable values for current truth table row |
rows.0.inputs.A | number | 0 | |
rows.0.inputs.B | number | 0 | |
rows.0.inputs.C | number | 0 | |
rows.0.inputs.D | number | 0 | |
rows.0.inputs.N | number | 0 | |
rows.0.inputs.O | number | 0 | |
rows.0.inputs.R | number | 0 | |
rows.0.result | number | 0 | Boolean result (0 or 1) for given input combination |
asciiTablePremium | string | | A | B | C | D | N | O | R | Result |
|---------… | ASCII formatted table representation for easy display |
Why ground on it
A model can produce something that looks like this answer from its training data, and be confidently out of date or simply wrong. This source returns the current value in a shape you can check, which is the difference between an answer you can cite and one you have to hedge.
Point an evaluation at rows.0.inputs.A: it is the field most worth pinning a claim to, and it is either present and current or absent — never plausibly invented.
Failure modes
Errors come back as tool errors carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.
| Status | What it means |
|---|---|
400 / 422 | The arguments did not validate. The message names the offending one. |
401 | The OAuth session is invalid or expired — reconnect the server. |
403 | Blocked by a key restriction or an IP allow-list. Never a bad identity. |
404 | This source is not part of VerveContext. Check the catalog. |
429 | Out of credits, or a brief rate limit. The message tells them apart. |
A call costs 2 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.
Use cases
- Computer Science Education
- Teach boolean logic and truth tables with interactive expression evaluation
- Digital Logic Design
- Verify logic gate combinations and circuit behavior for hardware design
- Boolean Expression Verification
- Test and validate complex boolean expressions programmatically
- Programming Logic Testing
- Debug and verify conditional logic in software applications
Other ways to use Truth Table Generation for AI Agents
Set up Truth Table Generation for AI Agents on VerveContext, or reach the same source a different way. Your VerveContext account and credits work on all of them — one key, one balance.
Call it as a REST APIOne HTTPS endpoint and an x-api-key header, with SDKs for Node, Python and .NET.APIVerve →Reference →
Give it to an AI agentConnect over MCP and your agent calls it as a native tool — Claude, Cursor, ChatGPT.VerveKit →Reference →
Google Sheets or ExcelA =VERVE() formula fills a column — no script, no export, recalculates in place.VerveSheets →Reference →
Related
More in Math/Calculations:
UTM Coordinate Conversion for AI AgentsConvert between UTM and latitude/longitudeColor Similarity for AI AgentsCalculate similarity between two colorsDaylight Duration Grounding DataCalculate daylight hours for any locationFibonacci Generation for AI AgentsGenerate Fibonacci sequence numbersPermutation & Combination for AI AgentsCalculate permutations and combinationsRoman Numeral Math for AI AgentsPerform math operations with Roman numerals