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TrendsAGI MCP Server

Developer ToolsModerate5.2MCP RegistryLocalRemote
Free

Server data from the Official MCP Registry

Trend data, insights and recommendations for AI agents. Read-only, with an Agent Skill.

About

Trend data, insights and recommendations for AI agents. Read-only, with an Agent Skill.

Remote endpoints: streamable-http: https://api.trendsagi.com/mcp

Security Report

5.2
Moderate5.2Moderate Risk

TrendsAGI is a legitimate trend-intelligence client, CLI, and MCP server that requires a TRENDSAGI_API_KEY, keeps tools read-only by default, and stores saved credentials with restrictive file permissions. The visible code shows no exfiltration, hardcoded secrets, or shell injection; the main considerations are network_http and local credential file access, both consistent with its purpose, plus the truncated portions of the code that could not be fully reviewed. Supply chain analysis found 6 known vulnerabilities in dependencies (0 critical, 1 high severity).

6 files analyzed · 11 issues found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Required

This plugin requests these system permissions. Most are normal for its category.

HTTP Network Access

Connects to external APIs or services over the internet.

File System Read

Reads files on your machine. Normal for tools that analyze or process local data.

File System Write

Writes or modifies files on your machine. Check that this is expected for the tool.

env_vars

Check that this permission is expected for this type of plugin.

process_spawn

Check that this permission is expected for this type of plugin.

How to Install & Connect

Available as Local & Remote

This plugin can run on your machine or connect to a hosted endpoint. during install.

Documentation

View on GitHub

From the project's GitHub README.

TrendsAGI

PyPI Version npm Version Python Versions License: MIT

Real-time trend intelligence for your code and your AI agents: what is trending on social platforms right now, with measured volume, velocity and growth, AI insights on why each topic is moving, evidence-backed recommendations, crisis alerts and watchlists. Paid media and growth teams use it to target what is rising, time spend to the trend curve and brief creative on measured demand.

Python clientTrendsAGIClient, a typed REST client
Command linetrendsagi, one command per API action, tables in a terminal and JSON in a pipe
Agent toolsTrendsAGITools for OpenAI, Claude, LangChain and WebMCP
Hosted MCP serverhttps://api.trendsagi.com/mcp for Claude, ChatGPT, Grok, Cursor and Gemini CLI
Cursor Agent SDKA ready agent project in agent-sdk/: one connection file gives an Agent SDK agent every hosted tool
Browser agents (WebMCP)Signed in to app.trendsagi.com, your browser's agent gets the same tools (webmcp/)
Local MCP servertrendsagi mcp, the same tools over stdio
PluginsClaude, Grok, Cursor and Snowflake Cortex Code plugin in plugins/trendsagi, Gemini CLI extension at the repo root
Ad executionExecutors that preview, then apply, Google, Meta, TikTok and LinkedIn ad changes from your own infrastructure

Install

pip install trendsagi            # client, agent tools and the trendsagi command
pip install "trendsagi[mcp]"     # adds the local MCP server (Python 3.10+)
pipx install trendsagi           # just the command line, in its own environment
npx trendsagi --help             # or the same command line from npm (Node.js 18+)

Create an API key under Profile > API Keys at app.trendsagi.com and export it:

export TRENDSAGI_API_KEY="your_api_key"

Quickstart

import os
from trendsagi import TrendsAGIClient

client = TrendsAGIClient(api_key=os.environ["TRENDSAGI_API_KEY"])

# Fastest-moving Technology topics right now
trends = client.get_trends(category="Technology", sort_by="velocity", limit=5)
for trend in trends.trends:
    print(trend.id, trend.name, trend.volume)

# Why is the top one moving?
insight = client.get_ai_insights(trends.trends[0].id)
if insight:
    print(insight.sentiment_summary, insight.key_themes)

Command line

trendsagi login                  # paste an API key; saved to ~/.config/trendsagi/config.json
trendsagi trends list --category Technology --sort velocity --limit 10
trendsagi insights get 123       # audience, sentiment and marketing angles
trendsagi sql "SELECT category, count(*) FROM trends GROUP BY 1 ORDER BY 2 DESC"
trendsagi recommendations list --priority high
trendsagi watchlist add "oat milk" --threshold 50000 --email
trendsagi api /api/integrations/delivery/health -q lookback_hours=24   # any endpoint
CommandsWhat they do
login, logout, whoamiSave, forget and check the API key
trends list get analytics categories autocompleteTrending topics with measured volume, velocity and growth
insights get generate [--wait] status searchAI insights per trend
recommendations list action feedbackEvidence-backed recommendations and their workflow status
crisis list actionCrisis events: acknowledge, archive, reopen
watchlist list add removeTracked keywords and categories, with alerts
sql, schemaOne read-only PostgreSQL SELECT over your data, and the tables it can read
tools list call, findThe agent tools, and whether TrendsAGI can do a task
webhooks, exportsCreate, change, test and run webhooks and data exports
ads providers resources preview apply report report-exportConnected ad platforms: trend-based changes and reports
integrations availability status health valueIntegration status and delivery health
streamLive trend updates as JSON lines
usage, status, apiAPI usage, service status, and any endpoint without its own command

Every command has --help. In a terminal, lists print as tables; piped or with --json they print JSON, so trendsagi trends list | jq works. The key comes from --api-key, then TRENDSAGI_API_KEY, then the saved login. Commands that delete something or change live ads ask first; pass --yes in scripts. Exit codes: 0 success, 1 API error, 2 invalid usage, 4 missing or rejected key.

The commands are declared once in src/trendsagi/cli_spec.json; a dependency-free Node.js build of the same CLI lives in npm/ and is published as trendsagi on npm. Guide: trendsagi.com/api-docs/integrations/cli.

The client calls any endpoint too: client.request("GET", "/api/integrations/delivery/health", params={"lookback_hours": 24}).

Use TrendsAGI in your AI assistant (no install)

Add the hosted MCP server, sign in to TrendsAGI and approve the connection:

AssistantSetup
ClaudeOpen TrendsAGI in the Claude directory, or Settings > Connectors > Add custom connector with the URL below
Claude Codeclaude mcp add --transport http trendsagi https://api.trendsagi.com/mcp, or /plugin marketplace add TrendsAGI/TrendsAGI then /plugin install trendsagi@trendsagi
ChatGPTAdd a custom connector with the URL below
GrokInstall the TrendsAGI plugin, or add the URL as a remote MCP server
Cursor{ "mcpServers": { "trendsagi": { "url": "https://api.trendsagi.com/mcp" } } }
Snowflake Cortex Codecortex mcp add trendsagi https://api.trendsagi.com/mcp --type http, or cortex plugin install github:TrendsAGI/TrendsAGI/plugins/trendsagi
Gemini CLIgemini extensions install https://github.com/TrendsAGI/TrendsAGI
https://api.trendsagi.com/mcp

Then ask "What is accelerating fastest in Technology this week, and who should I target with it?" The hosted tools are read-only, and each call counts as one API request. Each connection gets its own key, listed as "AI connector: " under Profile > API Keys; delete it to disconnect. Clients without OAuth can send an API key as Authorization: Bearer <key>. Guide: trendsagi.com/mcp.

The hosted server also publishes the TrendsAGI paid-media skill over MCP (SEP-2640) at skill://trendsagi/SKILL.md. Clients that support the io.modelcontextprotocol/skills extension discover it with skills/list and load it with resources/read; the manifest carries a SHA-256 digest and byte size for every file. Clients without the extension still receive the server instructions and tool descriptions, and the plugin distributions keep a bundled copy of the skill.

Build an agent with Cursor Agent SDK

Agent SDK defines agents as a folder of Markdown and TypeScript. Add TrendsAGI with one file and the agent gets the hosted MCP server's read-only tools by name:

// bot/mcp-connections/trendsagi.ts
import { defineConnection } from "@grok/agent-sdk/connections";

export default defineConnection({
  url: "https://api.trendsagi.com/mcp",
  headers: { authorization: "Bearer ${TRENDSAGI_API_KEY}" },  // filled by Agent SDK, not JavaScript
  advertiseTools: true,
  effects: "read",
});
agent-sdk run --dir . --message "What is rising fastest in Technology this week?"

agent-sdk/ is a complete project to copy: instructions, a trend-brief skill, hosting settings (egress to api.trendsagi.com, a TRENDSAGI_API_KEY secret) and smoke evals. Guide: trendsagi.com/api-docs/integrations/agent-sdk.

Use TrendsAGI from your browser's agent (WebMCP)

WebMCP lets a web page hand tools to the AI agent built into the browser (Chrome and Edge in origin trials, ChatGPT desktop, Brave Leo). While you are signed in to app.trendsagi.com, the app registers TrendsAGI's read-only tools with document.modelContext, so the agent uses them with your session: no connector or API key, and calls count as app use rather than API usage. trendsagi.com offers public tools (docs search, trend reports, plans and the free calculators) to every visitor.

To put TrendsAGI tools on your own site, register them in your page and run them on your server, which keeps the API key:

tools = TrendsAGITools(TrendsAGIClient(api_key=os.environ["TRENDSAGI_API_KEY"]))

tools.webmcp()                     # serve to your page: name, title, description, inputSchema, annotations
tools.call("list_trends", args)    # run the call your page forwards

webmcp/ has the browser module and a FastAPI server. Guide: trendsagi.com/webmcp.

Agent tools

One registry, every format. The tools are read-only by default; add_to_watchlist and update_recommendation appear only with allow_writes=True (or trendsagi mcp --allow-writes).

ToolWhat the agent gets
list_trendsTrending topics by category or phrase, sorted by velocity, growth or volume
list_trend_categoriesValid category names
search_trend_insightsTrends and insights matching a theme
get_trend / get_trend_analyticsOne trend and its volume time series
get_trend_ai_insightsSummary, key themes, sentiment, audience, marketing angles
list_recommendationsEvidence-backed actions with a decision brief
list_crisis_eventsReputation and crisis events for monitored topics
list_watchlist / get_api_usageWatched topics and remaining daily quota
read_data_schema / execute_sqlRead-only SQL for questions that need filters, joins or aggregation
find_capabilityWhether TrendsAGI can do a task, and which tool or app page does it

OpenAI

import json, os
from openai import OpenAI
from trendsagi import TrendsAGIClient, TrendsAGITools

tools = TrendsAGITools(TrendsAGIClient(api_key=os.environ["TRENDSAGI_API_KEY"]))
openai = OpenAI()
messages = [{"role": "user", "content": "Find a fast-rising Technology trend and suggest a campaign angle."}]

while True:
    reply = openai.chat.completions.create(model="gpt-5-mini", messages=messages, tools=tools.openai())
    message = reply.choices[0].message
    messages.append(message)
    if not message.tool_calls:
        print(message.content)
        break
    for call in message.tool_calls:
        result = tools.call(call.function.name, call.function.arguments)
        messages.append({"role": "tool", "tool_call_id": call.id, "content": json.dumps(result)})

Claude, LangChain and others

tools.anthropic()         # Anthropic Messages API tools=
tools.openai_responses()  # OpenAI Responses API tools=
tools.langchain()         # LangChain StructuredTools (pip install "trendsagi[langchain]")
tools.webmcp()            # WebMCP descriptors for document.modelContext.registerTool

With Claude, pass tools=tools.anthropic() and answer each tool_use block with {"type": "tool_result", "tool_use_id": block.id, "content": json.dumps(tools.call(block.name, block.input))}. tools.call never raises: errors come back as {"error": ...} so the model can read a rate limit or a bad argument and recover.

Local MCP server

pip install "trendsagi[mcp]"
claude mcp add trendsagi --env TRENDSAGI_API_KEY=your_api_key -- trendsagi mcp

Or in any MCP client's JSON config (Claude Desktop, Cursor, VS Code):

{ "mcpServers": { "trendsagi": { "command": "trendsagi-mcp", "env": { "TRENDSAGI_API_KEY": "your_api_key" } } } }

The local server publishes the same skill as the hosted endpoint, at skill://trendsagi/SKILL.md, and declares the io.modelcontextprotocol/skills extension. It is read from the installed package, so it stays in step with the version of trendsagi you installed. Supporting references cover the tool surface, paid-media workflow, read-only SQL and error handling.

Query with SQL

For answers no single endpoint returns, such as growth by category or the trends that match a watchlist:

schema = client.get_data_schema()   # tables, columns, rules, examples
result = client.execute_sql(
    """
    SELECT category, count(*) AS trends, round(avg(growth_pct)::numeric, 1) AS avg_growth_pct
    FROM trends
    WHERE last_seen_at > now() - interval '7 days' AND growth_pct IS NOT NULL
    GROUP BY category ORDER BY avg_growth_pct DESC
    """,
    max_rows=20,
)
print(result["columns"], result["rows"])

Tables: trends, trend_snapshots (90 days of readings), trend_categories, trend_insights, watchlist, recommendations and crisis_events; the last three only contain your own account's rows. Queries are one validated SELECT, run read-only for at most 5 seconds, and count as one API request. A refused query raises exceptions.QueryError with a code (such as unknown_table or timeout), plus hint and position when known.

Recommendations with decision briefs

recommendations = client.get_recommendations(match_user_interests=True, priority="high", sort="priority", limit=10)
for rec in recommendations.recommendations:
    brief = rec.decision_brief
    if brief and brief.actionable:
        print(rec.title, brief.why_now, brief.next_steps[:1])

Each brief explains why an action is timely, the measured signals behind it and concrete next steps. Its confidence score measures evidence completeness, not the chance of success; use actionable and data_quality to hold back when signals are stale or incomplete.

Ad execution in your own infrastructure

GoogleAdsExecutor, MetaAdsExecutor, TikTokAdsExecutor and LinkedInAdsExecutor take credentials at runtime, use deterministic idempotency keys, and support dry-run previews and strict validation:

from trendsagi.integrations import GoogleAdsExecutor

insight = client.get_ai_insights(trend_id)  # the trend you decided to act on
google = GoogleAdsExecutor({
    "access_token": os.environ["GOOGLE_ADS_ACCESS_TOKEN"],
    "developer_token": os.environ["GOOGLE_ADS_DEVELOPER_TOKEN"],
})
# Positive keywords target an ad group; campaign criteria can only exclude.
preview = google.apply_targeting(
    insight,
    customer_id="1234567890",
    campaign_id="9876543210",
    ad_group_id="1122334455",
    dry_run=True,
    strict_mode=True,
)
print(preview.response)  # inspect before any real change

See INTEGRATIONS_BYOC.md for every executor.

Errors

from trendsagi import exceptions

try:
    client.get_trends(limit=5)
except exceptions.RateLimitError:
    ...  # back off and retry
except exceptions.AuthenticationError:
    ...  # invalid or revoked key

Other commands

trendsagi mcp [--allow-writes]                              # MCP server over stdio
trendsagi scaffold --type docker --output-dir ./runner      # executor runner template
trendsagi scaffold --type terraform --output-dir ./infra    # infrastructure template

Plans and limits

The free Developer plan includes one API key and 100 API calls a day; Advantage, Scale and Enterprise raise the daily limit and add keys and team features. Calls above the daily allowance are billed as overage. See pricing.

Links

License

MIT. See LICENSE.

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