Leadfeeder

Live

OAUTH 2.0

CRM & SALES

Analytics

Connect to Leadfeeder's MCP server to identify website visitors, track B2B leads, and surface company-level intent data directly from your AI workflows.

  • Acts as the user: Every tool call runs as the authorizing user. Access and audit trail stay intact.
  • Credentials stay vaulted: AES-256 encrypted, resolved at request time, never stored in LLM context.
  • Scoped before every call: Per-user permissions enforced automatically. 90-day audit trail included.
Leadfeeder
agent · Acme Q3
Run
Add Company To Lists in Leadfeeder
S
leadfeedermcp_add_company_to_lists
85ms
Leadfeeder agent
Allows the addition of this company to one or more lists. since lists are a separate entity, the ids that you must pass .
Sources: Leadfeeder
leadfeedermcpmcp
1 tool call
18:29
Message Claude...

Leadfeeder tools for AI agents

CALL ANY TOOL
12 tools covering add, assign.
leadfeedermcp_search_contacts
Search contacts
Search for contacts using filters such as name, email, company, or other attributes.
Parameters
Name
Type
Required
Description
account_id
string
Required
The Leadfeeder Account ID. The Account ID can be retrieved using the List Accounts endpoint.
affiliation
string
Optional
Determines how the contact is related to the company.
buyer_persona_ids
array
Optional
List of buyer persona IDs to use as a filter.
company_ids
array
Optional
Filter contacts by Leadfeeder company IDs.
departments
array
Optional
The departments the contact works in within the company.
emails
array
Optional
Filter contacts by email addresses.
filters
object
Optional
Filter down search results (combined with AND).
hierarchy_levels
array
Optional
Filter contacts by hierarchy level within the company.
page_cursor
string
Optional
Cursor for pagination. Use this value to fetch the next page of results.
page_size
integer
Optional
The number of items per page. Maximum is 100.
positions
array
Optional
Search in orig and en fields.
search_terms
array
Optional
Search in contact fullname and title fields.
leadfeedermcp_get_icp
Get icp
leadfeedermcp_search_companies
Search companies
leadfeedermcp_get_tag
Get tag
leadfeedermcp_search_web_visits
Search web visits
leadfeedermcp_get_icps
Get icps
leadfeedermcp_search_companies_signals
Search companies signals
leadfeedermcp_get_list
Get list
leadfeedermcp_get_tags
Get tags
leadfeedermcp_create_tag
Create tag
leadfeedermcp_get_lists
Get lists
leadfeedermcp_update_tag
Update tag
leadfeedermcp_get_company
Get company
leadfeedermcp_create_list
Create list
leadfeedermcp_get_contact
Get contact
leadfeedermcp_update_list
Update list
leadfeedermcp_get_campaign
Get campaign
leadfeedermcp_update_campaign
Update campaign
leadfeedermcp_get_contacts
Get contacts
leadfeedermcp_create_custom_field
Create custom field
leadfeedermcp_get_campaigns
Get campaigns
leadfeedermcp_update_custom_field
Update custom field
leadfeedermcp_get_company_ips
Get company ips
leadfeedermcp_add_company_to_lists
Add company to lists
leadfeedermcp_get_account_info
Get account info
leadfeedermcp_add_contact_to_lists
Add contact to lists
leadfeedermcp_get_custom_field
Get custom field
leadfeedermcp_create_company_enrichment_job
Create company enrichment job
leadfeedermcp_get_buyer_persona
Get buyer persona
leadfeedermcp_create_find_contact_data_job
Create find contact data job
Build your Agent
Same auth pattern across every framework.
Python · LlamaIndex
from langchain_mcp_adapters.client import MultiServerMCPClient
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="leadfeedermcp")

mcp = MultiServerMCPClient({
"leadfeedermcp": {
"url": "https://mcp.scalekit.com/leadfeedermcp",
"headers": {"Authorization": "Bearer " + token}
}
})
tools = await mcp.get_tools()
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "leadfeedermcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/leadfeedermcp
// Pass: Authorization: Bearer + token
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const client = new ScalekitClient({ envUrl, clientId, clientSecret });
const token = await client.agent.getToken({ userId: "user_id", connector: "leadfeedermcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/leadfeedermcp
// Pass: Authorization: Bearer + token
from google.adk.agents import LlmAgent
from scalekit import ScalekitClient

client = ScalekitClient(env_url=ENV_URL, client_id=CLIENT_ID, client_secret=SECRET)
token = client.agent.get_token(user_id="user_id", connector="leadfeedermcp")
# Connect to MCP at https://mcp.scalekit.com/leadfeedermcp
# Pass: Authorization: Bearer + token
Try these prompts
Paste any prompt into your agent to get started.
Get started
Copy the prompt
Copied
Retrieve current API usage and credit consumption for a Leadfeeder account?
Copy the prompt
Copied
Update the configuration of an existing web visit custom feed?
Advanced
Copy the prompt
Copied
Remove one or more tags from a Leadfeeder company?
Copy the prompt
Copied
Search and filter web visit records to identify companies that visited your website?
SEE HOW AUTH WORKS
User authorises once. Every agent call after uses their token with scope enforcement.
1
Authorize
Your user connects
Leadfeeder
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
2
Store
Their
Leadfeeder
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
3
Resolve
When your agent calls a
Leadfeeder
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
4
Audit
Every
Leadfeeder
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 connectors.
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.
GTM and RevOps Teams
Deal intelligence agent
Pulls recent Gong calls, scores deal risk with an LLM, cross-references the record in Attio, and DMs each owner their at-risk deals in Slack. Every read is scoped to that rep's own access.
Engineering Teams
Engineering standup agent
Pulls commits from GitHub and GitLab, tracks issue movement in Jira, and posts a per-engineer standup brief to Slack. Each engineer's activity is read on their own delegated OAuth.
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.
Test other agents
See the same per-user auth pattern across other connectors.
SALES
Deal intelligence agent
Score Gong call risk with an LLM, cross-reference the Attio record, and DM each owner their at-risk deals in Slack.
ENGINEERING
Engineering standup agent
Pull commits from GitHub and GitLab, track Jira issue movement, and post a per-engineer standup brief to Slack.
GTM
Revenue forecast agent
Score pipeline coverage against quota across Salesforce and HubSpot, post forecast commentary to Slack, log snapshots to Sheets.
GTM
Competitive intelligence briefing agent
Scan Gong calls for competitor mentions, match each one to its Notion battlecard, and DM every affected rep a single Slack digest.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
01.
Shared tokens break per-user analytics
A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential.
// shared token
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
One connector today. Ten 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 Leadfeeder as the user or as a shared key?
As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Leadfeeder OAuth token stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in Leadfeeder?
Yes. Pass a tool name filter to listScopedTools so the analytics agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Leadfeeder.

What happens when a user revokes Leadfeeder 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.

Which website visitor data can the agent read or tag?
Only Leadfeeder accounts the authorizing user belongs to. Company tagging, list changes, and enrichment jobs attribute to that user, keeping intent data inside the right team.

Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""leadfeedermcp"": {
""url"": ""https://mcp.scalekit.com/leadfeedermcp"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.leadfeedermcp]
url = ""https://mcp.scalekit.com/leadfeedermcp""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""leadfeedermcp"": {
""url"": ""https://mcp.scalekit.com/leadfeedermcp"",
""type"": ""http""
}
}
}