Legal Data Hunter MCP connector for AI agents

CALL ANY TOOL

7 tools covering get, discover.

legaldatahuntermcp_get_filters

Get filters

Get available filter values for a specific data source. Returns distinct courts, jurisdictions, chambers, decision types, languages, court tiers, and date ranges that can be used to refine search results. For sources spanning multiple namespaces, pass namespace to select which namespace's filters to return.

Parameters

Name

Type

Required

Description

source

string

Required

Source identifier to get filters for, e.g. "FR/Judilibre" or "AT/RIS".

namespace

string

Optional

Optional namespace : "case_law", "legislation", or "doctrine". Required for sources spanning multiple namespaces; otherwise the namespace with the most rows is used.

legaldatahuntermcp_search

Search

legaldatahuntermcp_get_document

Get document

legaldatahuntermcp_discover_sources

Discover sources

legaldatahuntermcp_resolve_reference

Resolve reference

legaldatahuntermcp_discover_countries

Discover countries

legaldatahuntermcp_report_source_issue

Report source issue

Build your Agent

Same auth pattern across every framework.

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="legaldatahuntermcp")

mcp = MultiServerMCPClient({
    "legaldatahuntermcp": {
        "url": "https://mcp.scalekit.com/legaldatahuntermcp",
        "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: "legaldatahuntermcp" });

const openai = new OpenAI();
// Connect to MCP at https://mcp.scalekit.com/legaldatahuntermcp
// 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: "legaldatahuntermcp" });

const anthropic = new Anthropic();
// Connect to MCP at https://mcp.scalekit.com/legaldatahuntermcp
// 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="legaldatahuntermcp")
# Connect to MCP at https://mcp.scalekit.com/legaldatahuntermcp
# Pass: Authorization: Bearer + token

Try these prompts

Paste any prompt into your agent to get started.

Get started

Copy the prompt

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Search the world’s fastest-growing legal database using hybrid semantic and keyword matching?

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Resolve a loose legal citation or reference to the exact matching document(s)?

Advanced

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Report an issue with a data source to the platform maintainer?

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Get available filter values for a specific data source?

SEE HOW AUTH WORKS

User authorises once. Every agent call after uses their token with scope enforcement.

1

Authorize

Your user connects

Legal Data Hunter 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

2

Store

Their

Legal Data Hunter 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

3

Resolve

When your agent calls a

Legal Data Hunter 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

4

Audit

Every

Legal Data Hunter 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 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

Outbound prospecting agent

Searches Apollo for prospects matching your ICP, scores and ranks them, drafts personalized outreach in Gmail, and logs every send to Google Sheets. Mail goes out as the rep, not from a shared inbox.

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.

Support and Ops Teams

Support triage agent

Fetches new Zendesk tickets, classifies them by type and urgency, searches the Notion knowledge base for an answer, and routes what it cannot resolve to Slack. Every call runs on the support agent's own delegated OAuth.

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.

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.

SALES

Outbound prospecting agent

Search Apollo for ICP matches, rank them, draft personalised Gmail outreach, and log every send to Google Sheets.

SUPPORT

Support triage agent

Classify new Zendesk tickets, search the Notion knowledge base for an answer, and route what it cannot resolve to Slack.

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 Legal Data Hunter 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 Legal Data Hunter 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 Legal Data Hunter?
Yes. Pass a tool name filter to listScopedTools so the research agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Legal Data Hunter.

What happens when a user revokes Legal Data Hunter 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 legal data sources can the agent search?
All sources indexed for the authorizing user's Legal Data Hunter account. Document retrieval and coverage queries run per user, keeping matter research attributable.

Legal Data Hunter MCP

Legal Data Hunter MCP tools for AI agents