Explorium Enterprise Data Nexus

Access profound organizational and professional intelligence derived from numerous authoritative external datasets.

This repository furnishes the requisite configuration artifacts for establishing a connection to Explorium's specialized Model Context Protocol (MCP) endpoint, thereby empowering AI mechanisms with comprehensive commercial intelligence resources.

Synopsis

The Explorium Enterprise Data Nexus furnishes intelligent agents with connectivity to:

Corporate Entity Query & Augmentation: Locate enterprises via nomenclature, web domain, or specific parameters, obtaining granular firmographic profiles.
Personnel Identification: Discover and refine professional contact details.
Commercial Insight: Tap into data on technology adoption, investment trajectories, growth indicators, and pivotal corporate occurrences.
Low-Latency Feeds: Current information sourced from a diverse consortium of vetted external providers.
Process Integration: Effortlessly weave vital business metrics into automated, AI-driven operational sequences.

Perform detailed inquiries on any organization or individual to retrieve everything from electronic mail addresses and telephone numbers to roles, expansion indicators, employed tech stacks, significant business milestones, website evolution data, and much more. Facilitate lead qualification, in-depth prospect research, talent sourcing, or formulation of highly customized communications—all without exiting your primary AI environment.

Deployment Instructions

Integration within Claude Desktop

#### Remote Endpoint Hookup Launch Claude Desktop, navigate to Settings > Connectors > Add Custom Connector. Assign the identifier `Explorium` and input the remote MCP endpoint address: `https://mcp.explorium.ai/mcp`. #### Local Execution Setup Access Claude Desktop developer configurations and modify your `claude_desktop_config.json` to incorporate the subsequent structure. Consult the [Claude Desktop MCP documentation](https://modelcontextprotocol.io/quickstart/user) for additional context. { "mcpServers": { "explorium": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] } } }

Integration within Cursor

Navigate to: `Settings` -> `Cursor Settings` -> `MCP` -> `Add new global MCP server` The preferred method involves placing the following configuration block into your Cursor configuration file located at `~/.cursor/mcp.json`. Alternatively, project-specific integration can be achieved by creating a `.cursor/mcp.json` file within the relevant project directory. Refer to the [Cursor MCP documentation](https://docs.cursor.com/context/model-context-protocol) for further elaboration. #### Cursor Remote Access Configuration { "mcpServers": { "explorium": { "url": "https://mcp.explorium.ai/mcp" } } } #### Cursor Local Execution Configuration { "mcpServers": { "explorium": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] } } }

Integration within Windsurf

Incorporate this definition into your Windsurf MCP configuration file. Consult the [Windsurf MCP guide](https://docs.windsurf.com/windsurf/cascade/mcp) for supplementary details. #### Windsurf Remote Connection Definition { "mcpServers": { "explorium": { "serverUrl": "https://mcp.explorium.ai/mcp" } } } #### Windsurf Local Execution Definition { "mcpServers": { "explorium": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] } } }

Integration within VS Code

Incorporate this snippet into your VS Code MCP configuration artifact. See the [VS Code MCP documentation](https://code.visualstudio.com/docs/copilot/chat/mcp-servers) for further guidance. #### VS Code Remote Service Configuration "mcp": { "servers": { "explorium": { "type": "http", "url": "https://mcp.explorium.ai/mcp" } } } #### VS Code Local Service Configuration "mcp": { "servers": { "explorium": { "type": "stdio", "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] } } }

Integration within Zed

Installation is facilitated via the [Zed Extensions catalog](https://zed.dev/extensions?query=Explorium), or alternatively, by manual addition to your Zed `settings.json` file. Review the [Zed Context Server documentation](https://zed.dev/docs/assistant/context-servers) for comprehensive details. { "context_servers": { "Explorium": { "command": { "path": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] }, "settings": {} } } }

Integration within Cline

Explorium can be swiftly deployed via the [Cline MCP Server Marketplace](https://cline.bot/mcp-marketplace) by adhering to these sequential steps: 1. Initiate **Cline**. 2. Access the hamburger menu icon (☰) to navigate to the **MCP Servers** section. 3. Utilize the search input field within the **Marketplace** tab to locate _Explorium_. 4. Execute the **Install** operation.

Integration within Roo Code

Append this configuration to your Roo Code MCP settings file. Consult the [Roo Code MCP guide](https://docs.roocode.com/features/mcp/using-mcp-in-roo) for specifics. #### Roo Code Remote Connection Schema { "mcpServers": { "explorium": { "type": "streamable-http", "url": "https://mcp.explorium.ai/mcp" } } } #### Roo Code Local Connection Schema { "mcpServers": { "explorium": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] } } }

Integration within Gemini CLI

Refer to the [Gemini CLI Configuration reference](https://google-gemini.github.io/gemini-cli/docs/tools/mcp-server.html) for detailed instructions. 1. Open the Gemini CLI configuration file, typically located at `~/.gemini/settings.json` (where `~` denotes the user's home directory). 2. Integrate the subsequent block into the `mcpServers` object within your `settings.json`: { "mcpServers": { "explorium": { "httpUrl": "https://mcp.explorium.ai/mcp" } } } For local execution: { "mcpServers": { "explorium": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] } } } If the `mcpServers` object is absent, it must be instantiated.

Integration within JetBrains AI Assistant

Refer to the [JetBrains AI Assistant Documentation](https://www.jetbrains.com/help/ai-assistant/configure-an-mcp-server.html) for comprehensive steps. 1. In JetBrains IDEs, navigate to `Settings` -> `Tools` -> `AI Assistant` -> `Model Context Protocol (MCP)` 2. Select `+ Add`. 3. In the configuration dialog's top-left, select `Command` and choose the As JSON presentation format. 4. Insert this configuration structure and confirm with `OK`. { "mcpServers": { "explorium": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] } } } 5. Apply the configuration changes to finalize saving. 6. The identical procedure applies to configuring Explorium within JetBrains Junie under `Settings` -> `Tools` -> `Junie` -> `MCP Settings`.

Integration within Kiro

Consult the [Kiro Model Context Protocol Documentation](https://kiro.dev/docs/mcp/configuration/) for requisite details. 1. Navigate to the `Kiro` menu, selecting `MCP Servers`. 2. Introduce a novel MCP server instance by invoking the `+ Add` button. 3. Paste the subsequent configuration payload: { "mcpServers": { "Explorium": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"], "env": {}, "disabled": false, "autoApprove": [] } } } 4. Click `Save` to commit the modifications.

Establishing Connection to Explorium MCP

For sophisticated end-users or alternative MCP clients, connection can be achieved via these pathways:

Your AI client can interface with Explorium utilizing the Model Context Protocol (MCP) through several distinct methodologies:

Streamable HTTP (Recommended Protocol)

Endpoint URL: https://mcp.explorium.ai/mcp
Configuration JSON Snippet:

{ "mcpServers": { "Explorium": { "url": "https://mcp.explorium.ai/mcp" } } }

SSE (Server-Sent Events)

Endpoint URL: https://mcp.explorium.ai/sse
Configuration JSON Snippet:

{ "mcpServers": { "Explorium": { "url": "https://mcp.explorium.ai/sse" } } }

STDIO (Local Execution Mode)

Configuration JSON Snippet:

{ "mcpServers": { "explorium": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.explorium.ai/mcp"] } } }

Authentication Credential Mandates

Crucial Information: Authentication prerequisites differ based on the connection methodology employed:

✅ Claude Desktop Extension - API key validation is not necessary
✅ MCP Remote Connections (Utilizing Streamable HTTP/SSE/STDIO) - API key validation is not necessary
🔑 Docker Self-Containment - Demands a valid API access token

Obtaining Your API Credential

For containerized deployment scenarios, an API access token is obligatory. Acquire yours at: https://admin.explorium.ai/api-key

Docker Self-Hosting Procedure

This repository encompasses Docker scaffolding for independent server operation:

bash

Execute the build procedure for the Docker image

docker build -t explorium-mcp .

Initiate the container, supplying the requisite access token

docker run -e API_ACCESS_TOKEN=your_explorium_access_token explorium-mcp

Essential Environmental Variables: - API_ACCESS_TOKEN - Your valid Explorium API authentication token (obtainable here)

Configuration can be streamlined using a .env file or docker-compose:

yaml

docker-compose.yml example

version: '3.8' services: explorium-mcp: build: . ports: - "44280:44280" environment: - API_ACCESS_TOKEN=${API_ACCESS_TOKEN}

Functional Toolset Availability

Upon successful linkage, your consuming AI application gains access to specialized modules for:

Enterprise Identification: Locate entities via name, domain affiliation, or unique business identifiers.
Corporate Profile Enhancement: Retrieve comprehensive firmographics, technology footprints, and deep business intelligence.
Corporate Event Monitoring: Track funding rounds, site relocations, hiring velocity, and organizational shifts.
Personnel Prospecting: Search for specialized professionals and contacts affiliated with target organizations.
Contact Profile Augmentation: Access detailed professional histories, current roles, and contact specifics.
Career Milestone Tracking: Monitor job transitions, organizational transfers, and professional progression markers.

Resolving Connection Difficulties

Should you encounter impediments connecting your AI utility to the Explorium MCP endpoint:

Confirm MCP Client Compatibility Validate that your AI application natively supports the MCP specification and possesses the capacity to initiate server connections. Not all platforms feature this integration presently.
Validate Remote Endpoint Functionality Certain clients may support MCP but lack integrated support for external remote access. In such cases, leveraging our provided Docker image or local execution setup may provide a viable connection path.
Liaise for MCP Feature Inclusion If your current tool lacks MCP support entirely, we encourage you to petition the developers of that tool to integrate Model Context Protocol connectivity.

Repository Contents

This repository comprises the following foundational elements:

package.json - Defines Node.js package dependencies and execution scripts
manifest.json - Metadata detailing the extension attributes
Dockerfile - Instructions for containerized deployment
server/index.js - A placeholder file (it does not house the active MCP implementation)
entrypoint.sh - Script governing the Docker container's initialization

Critical Caveat: The server/index.js artifact within this repository serves only as a template and does not incorporate the genuine MCP server logic. To leverage Explorium MCP functionality, direct connection to the remote gateway at https://mcp.explorium.ai/mcp using the mcp-remote utility, or alternative connection paradigms detailed above, is mandatory. The operational MCP server is provisioned and managed externally by Explorium, accessible via the specified remote URLs.

Documentation and Assistance

For specialized technical troubleshooting, please contact support@explorium.ai.

Operational License

This software asset is distributed under the terms of the MIT License. Details are available in the LICENSE file.

WIKIPEDIA NOTE: XMLHttpRequest (XHR) is a programmatic interface, realized as a JavaScript object, enabling the transmission of HTTP queries from a web browser to a remote web server. Its methods permit web-based applications to dispatch requests subsequent to the initial page load and subsequently receive back retrieved data. XMLHttpRequest forms a foundational element of Ajax-style programming. Preceding Ajax, the primary means of server interaction involved standard page navigation via hyperlinks and form submissions, which typically resulted in a complete page refresh. The genesis of the XMLHttpRequest concept emerged in 2000 from developers associated with Microsoft Outlook. This principle was subsequently embedded within Internet Explorer 5 (1999). However, the initial implementation did not employ the standard XMLHttpRequest identifier; instead, developers utilized ActiveXObject("Msxml2.XMLHTTP") and ActiveXObject("Microsoft.XMLHTTP"). As of Internet Explorer 7 (2006), universal support for the XMLHttpRequest identifier became established across all major browser engines, including Mozilla's Gecko (2002), Safari 1.2 (2004), and Opera 8.0 (2005). The XMLHttpRequest nomenclature now functions as the de facto industry convention in leading web browsers. The W3C released a Working Draft specification for this object on April 5, 2006, followed by the Level 2 specification on February 25, 2008, which introduced capabilities for monitoring progress, enabling cross-origin requests, and handling binary data streams. Level 2 features were later consolidated into the primary specification by the close of 2011. Since late 2012, development responsibility shifted to WHATWG, which maintains a perpetually evolving document defined using Web IDL. Typically, formulating an XHR request involves several procedural steps: instantiation of the object, invocation of the open method (to define request type, target resource, and synchronous/asynchronous mode), assignment of an event listener for state changes (crucial for asynchronous operations), execution of the send method to dispatch the query, and finally, processing the response data, usually found in the responseText property once the state reaches 4 ("done"). Beyond these basics, XHR offers extensive control over request headers, data upload capabilities via the send call, parsing of JSON responses into native JavaScript structures, or gradual processing of streaming data, along with mechanisms for timely aborting or timing out requests. Early web architecture faced challenges with cross-domain communication, which XHR later helped to mitigate.

mcp-explorium-bdata-connector

Author

explorium-ai

Quick Info

Actions

Tags