Lead Enrichment & Outreach LangGraph
blueprint · 4 agents · 4 MCP servers
1310★ stars
189forks
4.7rating
What it does
A web-enrichment agent and a CRM-lookup agent run in parallel on a new lead. A scorer combines what they find into a fit score against the ideal-customer profile and marks the lead qualified or not. Qualified leads flow to a drafter that writes a specific first-touch email grounded in the enrichment, and the workflow pauses for human approval before sending. Point the CRM server at your own instance and adjust the ICP.
The cast · 4 agents
Scorerscorerreasoning
Combine the web and CRM findings into a fit score against the ideal-customer profile. Return an object with a 'qualified' boolean, the score, and the top reasons. Do not qualify a lead that is already an active opportunity owned by someone else.
no tools · reasoning only
Drafterdrafterreasoning
Write a short, specific first-touch email grounded in the enrichment — reference something real about them, not a template. One clear ask. Save it as a draft; do not send.
mail.draft_email
CRM LookupcrmLookupfast
Look up the lead in the CRM. Report whether they or their company already exist, prior touches, deal stage, and owner. If new, say so.
crm.get_contactcrm.get_company
Web EnricherwebEnricherfast
Research the lead's company and role from the open web: what the company does, size signals, recent news, and the person's likely priorities. Report facts with sources. Do not guess.
search.web
Flow
⇉ parallel
→ Web Enricher → webData
→ CRM Lookup → crmData
→ Scorer → score
⑂ branch
score.qualified == true
→ Drafter → email
→ ask → outcome
Interface
Inputs
leadobject
The inbound lead: at least a name, email, and company.
Outputs
outcomestring
Whether the lead qualified and, if so, the approved email that was queued to send.
Depends on · 4 MCP servers
HubSpot MCPio.github.Servosity/hubspot-mcpcrmBVerified
io.github.brave/brave-search-mcpnot in the registry yetsearch
Multi-account MCP for Gmail, Calendar, Drive, Docs, and Sheets — 61 tools, tokenio.github.adelaidasofia/google-workspace-mcpmailAVerified
io.github.slack/slack-mcpnot in the registry yetchat⤓ Export runnable code
# Generated by @socketcat/compiler for target: langgraph
# blueprint: com.socketcat/lead-enrichment v1.0.0 schema: socketcat.dev/blueprint/v0
# This code is yours. Edit it freely. The socketcat_runtime helper is optional and can be vendored.
from typing import TypedDict
from langgraph.graph import StateGraph, START, END
import socketcat_runtime as _rt
class State(TypedDict, total=False):
lead: object
outcome: object
webData: object
crmData: object
score: object
email: object
def node_Fork_0(state):
return {}
def node_Join_1(state):
return {}
def node_AgentInvoke_2(state):
return _rt.run_agent("webEnricher", state, {"lead":"lead"}, "webData")
def node_AgentInvoke_3(state):
return _rt.run_agent("crmLookup", state, {"lead":"lead"}, "crmData")
def node_AgentInvoke_4(state):
return _rt.run_agent("scorer", state, {"crmData":"crmData","webData":"webData"}, "score")
def node_Branch_5(state):
return {}
def node_Join_6(state):
return {}
def node_AgentInvoke_7(state):
return _rt.run_agent("drafter", state, {"score":"score","webData":"webData"}, "email")
def node_Ask_8(state):
return _rt.run_ask("Review the drafted outreach email. Approve to queue it for send, or edit first.", state, "outcome")
def node_AgentInvoke_9(state):
return _rt.run_agent("scorer", state, {"score":"score"}, "outcome")
def route_Branch_5(state):
if _rt.cond("score.qualified == true", state): return "AgentInvoke_7"
return "AgentInvoke_9"
def build():
b = StateGraph(State)
b.add_node("Fork_0", node_Fork_0)
b.add_node("Join_1", node_Join_1)
b.add_node("AgentInvoke_2", node_AgentInvoke_2)
b.add_node("AgentInvoke_3", node_AgentInvoke_3)
b.add_node("AgentInvoke_4", node_AgentInvoke_4)
b.add_node("Branch_5", node_Branch_5)
b.add_node("Join_6", node_Join_6)
b.add_node("AgentInvoke_7", node_AgentInvoke_7)
b.add_node("Ask_8", node_Ask_8)
b.add_node("AgentInvoke_9", node_AgentInvoke_9)
b.add_edge(START, "Fork_0")
b.add_edge("Fork_0", "AgentInvoke_2")
b.add_edge("Fork_0", "AgentInvoke_3")
b.add_edge("Join_1", "AgentInvoke_4")
b.add_edge("AgentInvoke_2", "Join_1")
b.add_edge("AgentInvoke_3", "Join_1")
b.add_edge("AgentInvoke_4", "Branch_5")
b.add_conditional_edges("Branch_5", route_Branch_5, {"AgentInvoke_7": "AgentInvoke_7", "AgentInvoke_9": "AgentInvoke_9"})
b.add_edge("Join_6", END)
b.add_edge("AgentInvoke_7", "Ask_8")
b.add_edge("Ask_8", "Join_6")
b.add_edge("AgentInvoke_9", "Join_6")
return b.compile()
INPUTS = ["lead"]
OUTPUTS = ["outcome"]
if __name__ == "__main__":
_rt.main(build, INPUTS, OUTPUTS)
▸blueprint.json (the portable format)
{
"id": "com.socketcat/lead-enrichment",
"flow": {
"type": "sequence",
"blocks": [
{
"type": "parallel",
"blocks": [
{
"in": {
"lead": "lead"
},
"out": "webData",
"use": "webEnricher",
"type": "agent"
},
{
"in": {
"lead": "lead"
},
"out": "crmData",
"use": "crmLookup",
"type": "agent"
}
]
},
{
"in": {
"crmData": "crmData",
"webData": "webData"
},
"out": "score",
"use": "scorer",
"type": "agent"
},
{
"else": [
{
"in": {
"score": "score"
},
"out": "outcome",
"use": "scorer",
"type": "agent"
}
],
"type": "branch",
"cases": [
{
"when": "score.qualified == true",
"blocks": [
{
"in": {
"score": "score",
"webData": "webData"
},
"out": "email",
"use": "drafter",
"type": "agent"
},
{
"out": "outcome",
"type": "ask",
"prompt": "Review the drafted outreach email. Approve to queue it for send, or edit first."
}
]
}
]
}
]
},
"tags": [
"sales",
"lead-gen",
"orchestrator-workers",
"human-in-the-loop"
],
"title": "Lead Enrichment & Outreach",
"agents": {
"scorer": {
"model": {
"hint": "reasoning"
},
"title": "Scorer",
"output": {
"type": "object",
"required": [
"qualified"
],
"properties": {
"score": {
"type": "number"
},
"reasons": {
"type": "string"
},
"qualified": {
"type": "boolean"
}
}
},
"instructions": "Combine the web and CRM findings into a fit score against the ideal-customer profile. Return an object with a 'qualified' boolean, the score, and the top reasons. Do not qualify a lead that is already an active opportunity owned by someone else."
},
"drafter": {
"model": {
"hint": "reasoning"
},
"title": "Drafter",
"tools": [
"mail.draft_email"
],
"instructions": "Write a short, specific first-touch email grounded in the enrichment — reference something real about them, not a template. One clear ask. Save it as a draft; do not send."
},
"crmLookup": {
"model": {
"hint": "fast"
},
"title": "CRM Lookup",
"tools": [
"crm.get_contact",
"crm.get_company"
],
"instructions": "Look up the lead in the CRM. Report whether they or their company already exist, prior touches, deal stage, and owner. If new, say so."
},
"webEnricher": {
"model": {
"hint": "fast"
},
"title": "Web Enricher",
"tools": [
"search.web"
],
"instructions": "Research the lead's company and role from the open web: what the company does, size signals, recent news, and the person's likely priorities. Report facts with sources. Do not guess."
}
},
"estate": {
"email": {
"type": "object",
"description": "The drafter's tailored first-touch email."
},
"score": {
"type": "object",
"description": "The scorer's fit read, including a 'qualified' flag."
},
"crmData": {
"type": "object",
"description": "The CRM lookup's existing record and prior touches."
},
"webData": {
"type": "object",
"description": "The web enricher's firmographic and role findings."
}
},
"$schema": "socketcat.dev/blueprint/v0",
"authors": [
{
"url": "https://socketcat.com",
"name": "SocketCat"
}
],
"license": "MIT",
"servers": [
{
"ref": "io.github.Servosity/hubspot-mcp",
"alias": "crm"
},
{
"ref": "io.github.brave/brave-search-mcp",
"alias": "search"
},
{
"ref": "io.github.adelaidasofia/google-workspace-mcp",
"alias": "mail"
},
{
"ref": "io.github.slack/slack-mcp",
"alias": "chat"
}
],
"summary": "Enriches a new lead from the web and CRM in parallel, scores it against your ICP, and drafts a tailored first email for human approval.",
"targets": [
"langgraph",
"*"
],
"version": "1.0.0",
"interface": {
"inputs": {
"lead": {
"type": "object",
"description": "The inbound lead: at least a name, email, and company."
}
},
"outputs": {
"outcome": {
"type": "string",
"description": "Whether the lead qualified and, if so, the approved email that was queued to send."
}
}
},
"extensions": {
"dev.langgraph": {
"checkpointer": "memory"
}
},
"description": "A web-enrichment agent and a CRM-lookup agent run in parallel on a new lead. A scorer combines what they find into a fit score against the ideal-customer profile and marks the lead qualified or not. Qualified leads flow to a drafter that writes a specific first-touch email grounded in the enrichment, and the workflow pauses for human approval before sending. Point the CRM server at your own instance and adjust the ICP."
}