ai-mlanalytics-data

Chronulus MCP Server

chronulusai

by chronulusai

Integrate Chronulus AI forecasting & prediction agents with Claude for seamless AI forecasting, prediction tools, and fo

Enables integration of Chronulus AI Forecasting & Prediction Agents with Claude, allowing users to access AI-powered forecasting and prediction capabilities directly through Claude's interface.

github stars

105

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Requires Chronulus API keyDocker and pip installation options

best for

  • / Analysts needing forecasting capabilities in Claude
  • / Teams doing predictive modeling work
  • / Users wanting AI predictions without switching tools

capabilities

  • / Access Chronulus AI forecasting agents
  • / Generate AI-powered predictions
  • / Run forecasting models through Claude
  • / Integrate prediction workflows

what it does

Connects Claude to Chronulus AI's forecasting and prediction agents, enabling AI-powered forecasting capabilities directly within Claude conversations.

about

Chronulus MCP Server is an official MCP server published by chronulusai that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Chronulus AI forecasting & prediction agents with Claude for seamless AI forecasting, prediction tools, and fo It is categorized under ai ml, analytics data.

how to install

You can install Chronulus MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Chronulus MCP Server is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Chronulus AI

MCP Server for Chronulus

Chat with Chronulus AI Forecasting & Prediction Agents in Claude

### Quickstart: Claude for Desktop #### Install Claude for Desktop is currently available on macOS and Windows. Install Claude for Desktop [here](https://claude.ai/download) #### Configuration Follow the general instructions [here](https://modelcontextprotocol.io/quickstart/user) to configure the Claude desktop client. You can find your Claude config at one of the following locations: - macOS: `~/Library/Application Support/Claude/claude_desktop_config.json` - Windows: `%APPDATA%\Claude\claude_desktop_config.json` Then choose one of the following methods that best suits your needs and add it to your `claude_desktop_config.json`
Using pip (Option 1) Install release from PyPI ```bash pip install chronulus-mcp ``` (Option 2) Install from Github ```bash git clone https://github.com/ChronulusAI/chronulus-mcp.git cd chronulus-mcp pip install . ``` ```json { "mcpServers": { "chronulus-agents": { "command": "python", "args": ["-m", "chronulus_mcp"], "env": { "CHRONULUS_API_KEY": "" } } } } ``` Note, if you get an error like "MCP chronulus-agents: spawn python ENOENT", then you most likely need to provide the absolute path to `python`. For example `/Library/Frameworks/Python.framework/Versions/3.11/bin/python3` instead of just `python`
Using docker Here we will build a docker image called 'chronulus-mcp' that we can reuse in our Claude config. ```bash git clone https://github.com/ChronulusAI/chronulus-mcp.git cd chronulus-mcp docker build . -t 'chronulus-mcp' ``` In your Claude config, be sure that the final argument matches the name you give to the docker image in the build command. ```json { "mcpServers": { "chronulus-agents": { "command": "docker", "args": ["run", "-i", "--rm", "-e", "CHRONULUS_API_KEY", "chronulus-mcp"], "env": { "CHRONULUS_API_KEY": "" } } } } ```
Using uvx `uvx` will pull the latest version of `chronulus-mcp` from the PyPI registry, install it, and then run it. ```json { "mcpServers": { "chronulus-agents": { "command": "uvx", "args": ["chronulus-mcp"], "env": { "CHRONULUS_API_KEY": "" } } } } ``` Note, if you get an error like "MCP chronulus-agents: spawn uvx ENOENT", then you most likely need to either: 1. [install uv](https://docs.astral.sh/uv/getting-started/installation/) or 2. Provide the absolute path to `uvx`. For example `/Users/username/.local/bin/uvx` instead of just `uvx`
#### Additional Servers (Filesystem, Fetch, etc) In our demo, we use third-party servers like [fetch](https://github.com/modelcontextprotocol/servers/tree/main/src/fetch) and [filesystem](https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem). For details on installing and configure third-party server, please reference the documentation provided by the server maintainer. Below is an example of how to configure filesystem and fetch alongside Chronulus in your `claude_desktop_config.json`: ```json { "mcpServers": { "chronulus-agents": { "command": "uvx", "args": ["chronulus-mcp"], "env": { "CHRONULUS_API_KEY": "" } }, "filesystem": { "command": "npx", "args": [ "-y", "@modelcontextprotocol/server-filesystem", "/path/to/AIWorkspace" ] }, "fetch": { "command": "uvx", "args": ["mcp-server-fetch"] } } } ``` #### Claude Preferences To streamline your experience using Claude across multiple sets of tools, it is best to add your preferences to under Claude Settings. You can upgrade your Claude preferences in a couple ways: * From Claude Desktop: `Settings -> General -> Claude Settings -> Profile (tab)` * From [claude.ai/settings](https://claude.ai/settings): `Profile (tab)` Preferences are shared across both Claude for Desktop and Claude.ai (the web interface). So your instruction need to work across both experiences. Below are the preferences we used to achieve the results shown in our demos: ``` ## Tools-Dependent Protocols The following instructions apply only when tools/MCP Servers are accessible. ### Filesystem - Tool Instructions - Do not use 'read_file' or 'read_multiple_files' on binary files (e.g., images, pdfs, docx) . - When working with binary files (e.g., images, pdfs, docx) use 'get_info' instead of 'read_*' tools to inspect a file. ### Chronulus Agents - Tool Instructions - When using Chronulus, prefer to use input field types like TextFromFile, PdfFromFile, and ImageFromFile over scanning the files directly. - When plotting forecasts from Chronulus, always include the Chronulus-provided forecast explanation below the plot and label it as Chronulus Explanation. ```

FAQ

What is the Chronulus MCP Server MCP server?
Chronulus MCP Server is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Chronulus MCP Server?
This profile displays 55 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.655 reviews
  • Pratham Ware· Dec 16, 2024

    According to our notes, Chronulus MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Alexander Rao· Dec 16, 2024

    Chronulus MCP Server reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Diya Wang· Dec 12, 2024

    According to our notes, Chronulus MCP Server benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Mateo Khanna· Dec 8, 2024

    Chronulus MCP Server has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Aditi Patel· Dec 8, 2024

    Useful MCP listing: Chronulus MCP Server is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Min Kapoor· Dec 4, 2024

    Strong directory entry: Chronulus MCP Server surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Ren Garcia· Nov 27, 2024

    Chronulus MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Xiao White· Nov 23, 2024

    Chronulus MCP Server is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Mateo Kapoor· Nov 7, 2024

    We wired Chronulus MCP Server into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Mateo Dixit· Oct 26, 2024

    Chronulus MCP Server is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

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