Overview
Submit a raw emoji character, descriptive tag, or one of ten supported categories such as food or animals. The service queries matching records and returns matching characters with their official descriptions and category groupings. Paid plans add Unicode standard versions, iOS release compatibility, code points, aliases, and associated tags.
Live Test Emoji Grounding Data for AI Agents Source →
The tool
Once your client is connected to the VerveContext server, this appears in its tool list as EmojiGroundingDataforAIAgents. 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": "EmojiGroundingDataforAIAgents",
"arguments": {
"emoji": "🥳"
}
}You do not name the tool yourself; the model picks it. Asking about 🥳 in the terms this source covers is enough for it to reach for EmojiGroundingDataforAIAgents 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 |
|---|---|---|
emojiRequired | string | The emoji for which you want to get the text representation (e.g., 🥳) |
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": {
"count": 1,
"emojisFound": [
{
"emoji": "🥳",
"description": "partying face",
"category": "Smileys & Emotion",
"aliases": [
"partying_face"
],
"tags": [
"celebration",
"birthday"
],
"unicode_version": "11.0",
"ios_version": "12.1",
"codePoint": "1f973"
}
]
}
}
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 |
|---|---|---|---|
count | number | 1 | Number of emoji results found in response |
emojisFound | array[1] | Array of emoji objects with detailed information | |
emojisFound.0.emoji | string | 🥳 | The emoji character symbol |
emojisFound.0.description | string | partying face | Human-readable description of the emoji |
emojisFound.0.category | string | Smileys & Emotion | Emoji category classification for organization |
emojisFound.0.aliasesPremium | array | ["partying_face"] | Alternative names for the emoji |
emojisFound.0.tagsPremium | array | ["celebration","birthday"] | Tags describing emoji meaning and usage |
emojisFound.0.unicode_versionPremium | string | 11.0 | Unicode standard version where emoji was introduced |
emojisFound.0.ios_versionPremium | string | 12.1 | iOS version when emoji was first supported |
emojisFound.0.codePointPremium | string | 1f973 | Hexadecimal Unicode code point value. Emoji made of several code points - flags, ZWJ sequences, skin-tone variants - list all of them separated by spaces, e.g. "1f1fa 1f1f8" for the US flag |
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 count: 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
- Screen Reader Alt Text
- To generate accessible image labels, content systems map raw emoji to their official descriptions so screen readers pronounce every character accurately.
- Emoji Autocomplete Menus
- Chat applications search emoji tags and categories to populate keyboard suggestions and picker dropdowns while users type messages.
- Social Feedback Triage
- When evaluating incoming comments, sentiment pipelines convert raw emoji symbols into text descriptions before running rule-based classifiers.
- Topic Icon Categorization
- Before displaying user-submitted topic icons, community forums look up category classifications to sort discussion badges into matching sections.
Other ways to use Emoji Grounding Data for AI Agents
Set up Emoji Grounding Data 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.
Related
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