LunarCrush MCP connector for AI agents

Tools your market research agent reaches for on LunarCrush, scoped per user.

CALL ANY TOOL

15 read-only tools for social analytics: rank cryptocurrencies and stocks by social metrics, pull top posts, and track topics, keywords, and creators over time.

lunarcrushmcp_auth

Auth

Check subscription and rate limit information for the current API key, or test an alternate API key.

Parameters

Name

Type

Required

Description

apiKey

string

Optional

Optional alternate API key to use for this request.

lunarcrushmcp_creator

Creator

lunarcrushmcp_creator_posts

Creator posts

lunarcrushmcp_creator_time_series

Creator time series

lunarcrushmcp_cryptocurrencies

Cryptocurrencies

lunarcrushmcp_fetch

Fetch

lunarcrushmcp_keyword_posts

Keyword posts

lunarcrushmcp_keyword_time_series

Keyword time series

lunarcrushmcp_list

List

lunarcrushmcp_post

Post

lunarcrushmcp_search

lunarcrushmcp_stocks

Stocks

lunarcrushmcp_topic

Topic

lunarcrushmcp_topic_posts

Topic posts

lunarcrushmcp_topic_time_series

Topic time series

Build your Agent

Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.

import { ScalekitClient } from "@scalekit-sdk/node";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

// LunarCrush MCP tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["lunarcrushmcp"], toolNames: [
    "lunarcrushmcp_cryptocurrencies",
    "lunarcrushmcp_topic",
    "lunarcrushmcp_topic_posts",
    "lunarcrushmcp_topic_time_series"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "Which cryptocurrencies lead on social metrics right now?" }] });

import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["lunarcrushmcp"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Which cryptocurrencies lead on social metrics right now?" }],
  tools,
});

// Execute the tool call with the user's vaulted LunarCrush token
await sk.tools.executeTool(res.choices[0].message.tool_calls[0], "user_123");

import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["lunarcrushmcp"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Which cryptocurrencies lead on social metrics right now?" }],
  tools,
});

// Tool call runs with the user's vaulted LunarCrush token
await sk.tools.executeTool(msg.content, "user_123");

import { Agent } from "@google/adk/agents";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["lunarcrushmcp"] }, pageSize: 100,
});

const agent = new Agent({
  name: "market_research_agent",
  model: "gemini-2.5-pro",
  instruction: "LunarCrush MCP tools scoped to this user",
  tools,
});

await agent.run("Which cryptocurrencies lead on social metrics right now?");

Try these prompts

Copy any prompt into your agent. Each maps directly to a LunarCrush MCP tool. Click to copy, paste into your agent, done.

Crypto and stocks

Copy the prompt

Copied

List the top 10 cryptocurrencies by social metrics.

Copy the prompt

Copied

Rank technology sector stocks by social metrics.

Copy the prompt

Copied

Show DeFi coins sorted by social activity.

Topics and keywords

Copy the prompt

Copied

Give me a social snapshot of the bitcoin topic.

Copy the prompt

Copied

Show the top posts about Solana from the last 24 hours.

Copy the prompt

Copied

Chart social metrics for the keyword ETF approval over the past month.

Creators and posts

Copy the prompt

Copied

Summarize social metrics for this creator by screen name.

Copy the prompt

Copied

Get the top posts from this creator.

Copy the prompt

Copied

Show this creator's social metrics over the last 30 days.

SEE HOW AUTH WORKS

Each user signs in to LunarCrush once; Scalekit stores and refreshes their tokens. Every call is scope checked, and every action is logged.

Authorize

Your user connects

LunarCrush MCP

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

LunarCrush MCP

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

LunarCrush MCP

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

LunarCrush MCP

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

See the same per-user auth pattern across other analytics and market data connectors.

GTM and RevOps Teams

Competitive intelligence briefing agent

Scans Gong calls for competitor mentions, matches each one to its Notion battlecard, and DMs every affected rep a single Slack digest per cycle. Every call runs as the PMM who owns the briefing, never a shared bot.

GTM and RevOps Teams

Revenue forecast commentary

Pulls open pipeline from Salesforce and HubSpot, calculates coverage against quota, flags at-risk stages, posts commentary to Slack, and logs every snapshot to Google Sheets.

Engineering Teams

Slack triage

Polls Slack for new messages, classifies bugs and support requests with a LangGraph router, files GitHub issues or Zendesk tickets, and confirms in the thread.

Support and Ops Teams

Meeting prep

Pulls agenda, participant context, and open action items before every meeting.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared LunarCrush token looks fine in a demo. In production every social query looks like one service account, and you cannot tell which user triggered it. Scalekit resolves the credential of the actual user who triggered the agent, never a shared bot.

// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

LunarCrush today. Ten connectors tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access LunarCrush as the user or through a shared account?

As the user. Each user signs in to LunarCrush once, and Scalekit stores and refreshes their tokens. Audit logs attribute every social analytics query to that user, not a shared service account.

Where is the LunarCrush OAuth token stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Credentials never appear in prompts, logs, or LLM context.

Can I limit what the agent does in LunarCrush?

Yes. Filter by tool name in listScopedTools, for example only the topic and time series tools for a trend monitoring agent. Scalekit also enforces scope checks before every API call.

What happens when a user revokes LunarCrush access?

The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

What can the agent look up in LunarCrush?

Social metrics and top posts for cryptocurrencies, stocks, topics, keywords, and individual social accounts. All 15 tools are read-only: lunarcrushmcp_search finds topics, creators, and assets, lunarcrushmcp_topic returns a snapshot, and the time series tools return historical metrics.