Hookdeck MCP Server for LlamaIndexGive LlamaIndex instant access to 52 tools to Cancel Event, Count Connections, Count Sources, and more

Name: Hookdeck
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Hookdeck as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Ask AI about this MCP Server for LlamaIndex

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The Hookdeck MCP Server for LlamaIndex is a standout in the Developer Tools category — giving your AI agent 52 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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+ other MCP clients

python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Hookdeck. "
            "You have 52 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Hookdeck?"
    )
    print(response)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Hookdeck MCP Server

Connect your Hookdeck account to any AI agent to orchestrate your webhook infrastructure through natural conversation. Hookdeck provides the reliability layer for your event-driven architecture, and this server puts that power in your chat interface.

LlamaIndex agents combine Hookdeck tool responses with indexed documents for comprehensive, grounded answers. Connect 52 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Connection Management — List, create, and update connections that route webhooks from sources to destinations.
Traffic Control — Instantly pause or resume event routing for specific connections to manage maintenance windows or outages.
Source Monitoring — Retrieve and count your webhook sources to understand where your incoming data originates.
Lifecycle Operations — Enable or disable connections and manage their rules via JSON payloads without leaving your workflow.
Deep Inspection — Fetch specific metadata for any connection or source using unique IDs to debug routing issues.

The Hookdeck MCP Server exposes 52 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 52 Hookdeck tools available for LlamaIndex

When LlamaIndex connects to Hookdeck through Vinkius, your AI agent gets direct access to every tool listed below — spanning webhooks, event-driven, api-integration, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

cancel

Cancel event on Hookdeck

Cancel scheduled retries for an event

count

Count connections on Hookdeck

Count total connections

count

Count sources on Hookdeck

Count total sources

create

Create bookmark on Hookdeck

Create a new bookmark

create

Create connection on Hookdeck

Create a connection

create

Create destination on Hookdeck

Create a new destination

create

Create issue trigger on Hookdeck

Create a new issue trigger

create

Create source on Hookdeck

Create a new source

create

Create transformation on Hookdeck

Create a new transformation

delete

Delete bookmark on Hookdeck

Remove a bookmark

delete

Delete connection on Hookdeck

Permanently delete a connection

delete

Delete destination on Hookdeck

Delete a destination

delete

Delete issue trigger on Hookdeck

Delete an issue trigger

delete

Delete source on Hookdeck

Delete a source

disable

Disable connection on Hookdeck

Disable a connection

disable

Disable source on Hookdeck

Disable a source

enable

Enable connection on Hookdeck

Enable a disabled connection

enable

Enable source on Hookdeck

Enable a source

get

Get attempt on Hookdeck

Retrieve a specific attempt

get

Get connection on Hookdeck

Retrieve a specific connection

get

Get destination on Hookdeck

Retrieve a specific destination

get

Get event on Hookdeck

Retrieve a specific event

get

Get issue trigger on Hookdeck

Retrieve a specific issue trigger

get

Get metrics attempts on Hookdeck

Delivery attempt metrics

get

Get metrics events on Hookdeck

Event processing statistics

get

Get metrics queue depth on Hookdeck

Current queue depth per destination

get

Get metrics requests on Hookdeck

Request volume metrics

get

Get metrics transformations on Hookdeck

Transformation execution performance

get

Get request on Hookdeck

Retrieve a specific request

get

Get source on Hookdeck

Retrieve a specific source

get

Get transformation on Hookdeck

Retrieve a specific transformation

list

List attempts on Hookdeck

Retrieve a list of delivery attempts

list

List bookmarks on Hookdeck

Retrieve a list of bookmarks

list

List connections on Hookdeck

Retrieve a list of connections

list

List destinations on Hookdeck

Retrieve a list of destinations

list

List events on Hookdeck

Retrieve a list of events

list

List issue triggers on Hookdeck

Retrieve a list of issue triggers

list

List requests on Hookdeck

Retrieve a list of requests

list

List sources on Hookdeck

Retrieve a list of sources

list

List transformations on Hookdeck

Retrieve a list of transformations

pause

Pause connection on Hookdeck

Pause event routing for a connection

retry

Retry event on Hookdeck

Manually retry a failed event

retry

Retry request on Hookdeck

Retry a rejected request

test

Test transformation on Hookdeck

Test transformation code against a payload

trigger

Trigger bookmark on Hookdeck

Replay the bookmarked request

unpause

Unpause connection on Hookdeck

Resume event routing for a connection

update

Update connection on Hookdeck

Update a connection rules or name

update

Update destination on Hookdeck

Update destination config (URL, rate limit, etc.)

update

Update issue trigger on Hookdeck

Update an issue trigger

update

Update source on Hookdeck

Update a source

update

Update transformation on Hookdeck

Update transformation code

upsert

Upsert connection on Hookdeck

Create or update a connection by name

Connect Hookdeck to LlamaIndex via MCP

Follow these steps to wire Hookdeck into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 52 tools from Hookdeck

Why Use LlamaIndex with the Hookdeck MCP Server

LlamaIndex provides unique advantages when paired with Hookdeck through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Hookdeck tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Hookdeck tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Hookdeck, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Hookdeck tools were called, what data was returned, and how it influenced the final answer

Hookdeck + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Hookdeck MCP Server delivers measurable value.

Hybrid search: combine Hookdeck real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Hookdeck to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Hookdeck for fresh data

Analytical workflows: chain Hookdeck queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Hookdeck in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Hookdeck immediately.

"List all my current Hookdeck connections."

"Pause the connection with ID conn_456 immediately."

"How many webhook sources do I have?"

Troubleshooting Hookdeck MCP Server with LlamaIndex

Common issues when connecting Hookdeck to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Hookdeck + LlamaIndex FAQ

Common questions about integrating Hookdeck MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Hookdeck tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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