OpenClaw

Use Frontrun as a data source in your OpenClaw agent. Surface VC follow signals, convergence events, and classified entities directly in your agent's workflow.

Setup

Via MCP Server

Add to your OpenClaw agent's MCP configuration:

{
  "mcpServers": {
    "frontrun": {
      "command": "npx",
      "args": ["frontrun-mcp-server"],
      "env": {
        "FRONTRUN_API_KEY": "your_api_key"
      }
    }
  }
}

Your agent now has access to all Frontrun tools - tracking, convergence detection, classification, and search.

Via REST API

If your agent uses HTTP directly, call the REST API:

import requests
 
FRONTRUN = "https://frontrun.vc/v1"
HEADERS = {"X-API-Key": "your_api_key"}
 
# Get convergence signals
signals = requests.get(
    f"{FRONTRUN}/convergence",
    headers=HEADERS,
    params={"threshold": 3, "since": "7d"}
).json()

Agent Workflows

Daily deal flow monitor

Set your agent to check Frontrun daily and surface high-signal opportunities:

Agent prompt:
"Every morning, check Frontrun for:
1. Convergence signals (threshold 3+) from the last 24 hours
2. Trending entities with classification
3. Any new follows from [priority accounts]

Summarize findings and flag anything in the AI or DeFi sectors."

MCP tools used: frontrun_convergence, frontrun_trending, frontrun_new_follows

Automated classification pipeline

Let your agent build and maintain a custom classification layer:

Agent prompt:
"Create Frontrun classification rules for my investment thesis:
- AI Infrastructure: keywords 'inference', 'gpu cluster', 'model serving', 'llm ops'
- Developer Tools: keywords 'sdk', 'api platform', 'developer experience'
- DeFi: keywords 'defi', 'lending', 'amm', 'liquidity'

Then pull enriched follows weekly and flag anything matching these rules."

MCP tools used: frontrun_create_rule, frontrun_enriched_follows

VC activity tracker

Monitor specific investors for thesis changes:

Agent prompt:
"Track these VCs: @pmarca, @naval, @sequoia, @a16zcrypto
Every week, pull their activity profiles (90-day window).
Compare sector breakdowns week-over-week.
Alert me if any VC shows a >20% shift in sector attention."

MCP tools used: frontrun_vc_activity, frontrun_track

Research assistant

Use Frontrun data as context for deeper research:

Agent prompt:
"Search Frontrun for all AI startups in the follow graph.
For any company followed by 3+ tracked accounts, research:
- What do they build?
- Who are their competitors?
- What stage are they at?
Draft a one-paragraph brief for each."

MCP tools used: frontrun_search, frontrun_convergence, frontrun_classify

Available MCP Tools

All 36 tools, in one table. Credit costs are on the MCP server page.

Tool	Description
`frontrun_status`	Account status, balance, usage
`frontrun_track`	Start monitoring an X account
`frontrun_untrack`	Stop monitoring
`frontrun_list_tracked`	List monitored accounts
`frontrun_preview`	Evaluate an account before tracking: signal score, sector hints
`frontrun_new_follows`	New follows across tracked accounts
`frontrun_snapshot`	Current follow list for an account
`frontrun_convergence`	Multi-account convergence signals
`frontrun_trending`	Trending entities by attention
`frontrun_feed`	Real-time activity feed across tracked accounts
`frontrun_vc_activity`	Activity profile: velocity, sectors
`frontrun_vc_similar`	VCs with overlapping follow patterns
`frontrun_search`	Search by sector, keyword, type (tracked graph or full catalog)
`frontrun_thesis_search`	Plain-language investment thesis in, matching companies out
`frontrun_sectors`	Sector and entity-type breakdown of discovered entities
`frontrun_discover`	Accounts your tracked VCs follow that you're not tracking yet
`frontrun_reports`	Historical daily reports, filterable by date range and sector
`frontrun_company`	Synthesized company overview: what they do, sector, stage
`frontrun_company_founders`	Founder profiles for one company: name, role, background
`frontrun_founders_batch`	Founder lookup for up to 10 companies in one call
`frontrun_company_funding`	Round details and investors, cross-referenced with follow signal
`frontrun_company_signals`	Buzz score, sentiment, which tracked VCs follow them
`frontrun_company_resources`	Website, GitHub, docs, Discord, Telegram
`frontrun_enriched_follows`	New follows + classification + rules
`frontrun_classify`	On-demand entity classification
`frontrun_create_rule`	Create classification rule
`frontrun_list_rules`	List your rules
`frontrun_update_rule`	Update a rule
`frontrun_delete_rule`	Delete a rule
`frontrun_tag`	Tag an entity, or override its sector
`frontrun_list_tags`	List tagged entities
`frontrun_list_webhooks`	List registered webhooks with status and last delivery
`frontrun_create_webhook`	Register a webhook for new_follows / convergence events
`frontrun_delete_webhook`	Delete a webhook
`trending_teaser`	Free sample, no API key: top 5 trending companies from the last 7 days
`send_feedback`	No API key: report a confusing error, a missing capability, or a docs gap

Best Practices

Cache results - Data updates periodically, not in real time. Don't poll more than every 30 minutes.
Use convergence - It's the highest-signal endpoint. Threshold 3+ means multiple independent accounts noticed the same entity.
Build rules once - Classification rules persist. Set them up, then every /enriched call auto-applies them.
Monitor your balance - Call frontrun_status to check spend. Set up balance alerts to avoid interruptions.

MCP Server Claude Code