MCP ExplorerExplorer

Graphlit MCP Server

@graphliton 11 days ago
302 MIT
FreeOfficial
Knowledge Base
#mcp#graphlit#retrieval#extraction#ingestion#web#notifications
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. This document outlines the setup process and provides a basic example of using the client.

Overview

What is Graphlit MCP Server

The Model Context Protocol (MCP) Server is a tool that facilitates integration between MCP clients and the Graphlit platform, allowing users to consolidate various data sources into a searchable knowledge base. It processes different formats, including documents and media, and transforms them into accessible Markdown or transcribed text.

Use cases

The MCP Server can ingest data from multiple platforms such as Slack, Discord, Google Drive, and email, making it valuable for teams in software development and product management. It serves as a repository for relevant knowledge, assisting in tasks like search and retrieval of information across diverse tools and platforms.

How to use

To set up the MCP Server, users need Node.js and a Graphlit account. After configuring environment variables for authentication, the server can be installed through various IDEs or executed directly using NPX, with the necessary configurations specifying organization ID, environment ID, and JWT secret.

Key features

Key features include ingestion of various content types (e.g., files, messages), built-in web crawling and search capabilities, and publishing functionalities. Additionally, it supports multiple data connectors for popular applications and tools, enhancing its versatility for project integration.

Where to use

The Graphlit MCP Server can be employed in any MCP client application, such as Cursor, Windsurf, Cline, or integrated within team collaboration tools. It’s suitable for environments needing a central knowledge base, particularly in software development and management contexts, enabling access to information from various sources.

Content

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Model Context Protocol (MCP) Server for Graphlit Platform

Overview

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. This document outlines the setup process and provides a basic example of using the client.

Ingest anything from Slack, Discord, websites, Google Drive, email, Jira, Linear or GitHub into a Graphlit project - and then search and retrieve relevant knowledge within an MCP client like Cursor, Windsurf, Goose or Cline.

Your Graphlit project acts as a searchable, and RAG-ready knowledge base across all your developer and product management tools.

Documents (PDF, DOCX, PPTX, etc.) and HTML web pages will be extracted to Markdown upon ingestion. Audio and video files will be transcribed upon ingestion.

Web crawling and web search are built-in as MCP tools, with no need to integrate other tools like Firecrawl, Exa, etc. separately.

You can read more about the MCP Server use cases and features on our blog.

Watch our latest YouTube video on using the Graphlit MCP Server with the Goose MCP client.

For any questions on using the MCP Server, please join our Discord community and post on the #mcp channel.

graphlit-mcp-server MCP server

Tools

Retrieval

  • Query Contents
  • Query Collections
  • Query Feeds
  • Query Conversations
  • Retrieve Relevant Sources
  • Retrieve Similar Images
  • Visually Describe Image

RAG

  • Prompt LLM Conversation

Extraction

  • Extract Structured JSON from Text

Publishing

  • Publish as Audio (ElevenLabs Audio)
  • Publish as Image (OpenAI Image Generation)

Ingestion

  • Files
  • Web Pages
  • Messages
  • Posts
  • Emails
  • Issues
  • Text
  • Memory (Short-Term)

Data Connectors

  • Microsoft Outlook email
  • Google Mail
  • Notion
  • Reddit
  • Linear
  • Jira
  • GitHub Issues
  • Google Drive
  • OneDrive
  • SharePoint
  • Dropbox
  • Box
  • GitHub
  • Slack
  • Microsoft Teams
  • Discord
  • Twitter/X
  • Podcasts (RSS)

Web

  • Web Crawling
  • Web Search (including Podcast Search)
  • Web Mapping
  • Screenshot Page

Notifications

  • Slack
  • Email
  • Webhook
  • Twitter/X

Operations

  • Configure Project
  • Create Collection
  • Add Contents to Collection
  • Remove Contents from Collection
  • Delete Collection(s)
  • Delete Feed(s)
  • Delete Content(s)
  • Delete Conversation(s)
  • Is Feed Done?
  • Is Content Done?

Enumerations

  • List Slack Channels
  • List Microsoft Teams Teams
  • List Microsoft Teams Channels
  • List SharePoint Libraries
  • List SharePoint Folders
  • List Linear Projects
  • List Notion Databases

Resources

  • Project
  • Contents
  • Feeds
  • Collections (of Content)
  • Workflows
  • Conversations
  • Specifications

Prerequisites

Before you begin, ensure you have the following:

  • Node.js installed on your system (recommended version 18.x or higher).
  • An active account on the Graphlit Platform with access to the API settings dashboard.

Configuration

The Graphlit MCP Server supports environment variables to be set for authentication and configuration:

  • GRAPHLIT_ENVIRONMENT_ID: Your environment ID.
  • GRAPHLIT_ORGANIZATION_ID: Your organization ID.
  • GRAPHLIT_JWT_SECRET: Your JWT secret for signing the JWT token.

You can find these values in the API settings dashboard on the Graphlit Platform.

Installation

Installing via VS Code

For quick installation, use one of the one-click install buttons below:

Install with NPX in VS Code Install with NPX in VS Code Insiders

For manual installation, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).

Optionally, you can add it to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.

Note that the mcp key is not needed in the .vscode/mcp.json file.

{
  "mcp": {
    "inputs": [
      {
        "type": "promptString",
        "id": "organization_id",
        "description": "Graphlit Organization ID",
        "password": true
      },
      {
        "type": "promptString",
        "id": "environment_id",
        "description": "Graphlit Environment ID",
        "password": true
      },
      {
        "type": "promptString",
        "id": "jwt_secret",
        "description": "Graphlit JWT Secret",
        "password": true
      }
    ],
    "servers": {
      "graphlit": {
        "command": "npx",
        "args": [
          "-y",
          "graphlit-mcp-server"
        ],
        "env": {
          "GRAPHLIT_ORGANIZATION_ID": "${input:organization_id}",
          "GRAPHLIT_ENVIRONMENT_ID": "${input:environment_id}",
          "GRAPHLIT_JWT_SECRET": "${input:jwt_secret}"
        }
      }
    }
  }
}

Installing via Windsurf

To install graphlit-mcp-server in Windsurf IDE application, Cline should use NPX:

npx -y graphlit-mcp-server

Your mcp_config.json file should be configured similar to:

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "command": "npx",
            "args": [
                "-y",
                "graphlit-mcp-server"
            ],
            "env": {
                "GRAPHLIT_ORGANIZATION_ID": "your-organization-id",
                "GRAPHLIT_ENVIRONMENT_ID": "your-environment-id",
                "GRAPHLIT_JWT_SECRET": "your-jwt-secret",
            }
        }
    }
}

Installing via Cline

To install graphlit-mcp-server in Cline IDE application, Cline should use NPX:

npx -y graphlit-mcp-server

Your cline_mcp_settings.json file should be configured similar to:

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "command": "npx",
            "args": [
                "-y",
                "graphlit-mcp-server"
            ],
            "env": {
                "GRAPHLIT_ORGANIZATION_ID": "your-organization-id",
                "GRAPHLIT_ENVIRONMENT_ID": "your-environment-id",
                "GRAPHLIT_JWT_SECRET": "your-jwt-secret",
            }
        }
    }
}

Installing via Cursor

To install graphlit-mcp-server in Cursor IDE application, Cursor should use NPX:

npx -y graphlit-mcp-server

Your mcp.json file should be configured similar to:

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "command": "npx",
            "args": [
                "-y",
                "graphlit-mcp-server"
            ],
            "env": {
                "GRAPHLIT_ORGANIZATION_ID": "your-organization-id",
                "GRAPHLIT_ENVIRONMENT_ID": "your-environment-id",
                "GRAPHLIT_JWT_SECRET": "your-jwt-secret",
            }
        }
    }
}

Installing via Smithery

To install graphlit-mcp-server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @graphlit/graphlit-mcp-server --client claude

Installing manually

To use the Graphlit MCP Server in any MCP client application, use:

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "command": "npx",
            "args": [
                "-y",
                "graphlit-mcp-server"
            ],
            "env": {
                "GRAPHLIT_ORGANIZATION_ID": "your-organization-id",
                "GRAPHLIT_ENVIRONMENT_ID": "your-environment-id",
                "GRAPHLIT_JWT_SECRET": "your-jwt-secret",
            }
        }
    }
}

Optionally, you can configure the credentials for data connectors, such as Slack, Google Email and Notion.
Only GRAPHLIT_ORGANIZATION_ID, GRAPHLIT_ENVIRONMENT_ID and GRAPHLIT_JWT_SECRET are required.

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "command": "npx",
            "args": [
                "-y",
                "graphlit-mcp-server"
            ],
            "env": {
                "GRAPHLIT_ORGANIZATION_ID": "your-organization-id",
                "GRAPHLIT_ENVIRONMENT_ID": "your-environment-id",
                "GRAPHLIT_JWT_SECRET": "your-jwt-secret",
                "SLACK_BOT_TOKEN": "your-slack-bot-token",
                "DISCORD_BOT_TOKEN": "your-discord-bot-token",
                "TWITTER_TOKEN": "your-twitter-token",
                "GOOGLE_EMAIL_REFRESH_TOKEN": "your-google-refresh-token",
                "GOOGLE_EMAIL_CLIENT_ID": "your-google-client-id",
                "GOOGLE_EMAIL_CLIENT_SECRET": "your-google-client-secret",
                "LINEAR_API_KEY": "your-linear-api-key",
                "GITHUB_PERSONAL_ACCESS_TOKEN": "your-github-pat",
                "JIRA_EMAIL": "your-jira-email",
                "JIRA_TOKEN": "your-jira-token",
                "NOTION_API_KEY": "your-notion-api-key"
            }
        }
    }
}

NOTE: when running ‘npx’ on Windows, you may need to explicitly call npx via the command prompt.

"command": "C:\\Windows\\System32\\cmd.exe /c npx"

Support

Please refer to the Graphlit API Documentation.

For support with the Graphlit MCP Server, please submit a GitHub Issue.

For further support with the Graphlit Platform, please join our Discord community.

Tools

configureProject
Configures the default content workflow for the Graphlit project. Only needed if user asks to configure the default workflow. Optionally accepts whether to enable high-quality document and web page preparation using a vision LLM. Defaults to using Azure AI Document Intelligence for document preparation, if not assigned. Optionally accepts whether to enable entity extraction using LLM into the knowledge graph. Defaults to no entity extraction, if not assigned. Optionally accepts the preferred model provider service type, i.e. Anthropic, OpenAI, Google. Defaults to Anthropic if not provided. Returns the project identifier.
askGraphlit
Ask questions about the Graphlit API or SDKs. Can create code samples for any API call. Accepts an LLM user prompt for code generation. Returns the LLM prompt completion in Markdown format.
retrieveSources
Retrieve relevant content sources from Graphlit knowledge base. Do *not* use for retrieving content by content identifier - retrieve content resource instead, with URI 'contents://{id}'. Accepts an LLM user prompt for content retrieval. For best retrieval quality, provide only key words or phrases from the user prompt, which will be used to create text embeddings for a vector search query. Only use when there is a valid LLM user prompt for content retrieval, otherwise use queryContents. For example 'recent content' is not a useful user prompt, since it doesn't reference the text in the content. Accepts an optional ingestion recency filter (defaults to null, meaning all time), and optional content type and file type filters. Also accepts optional feed and collection identifiers to filter content by. Returns the ranked content sources, including their content resource URI to retrieve the complete Markdown text.
retrieveImages
Retrieve images from Graphlit knowledge base. Provides image-specific retrieval when image similarity search is desired. Do *not* use for retrieving content by content identifier - retrieve content resource instead, with URI 'contents://{id}'. Accepts image URL. Image will be used for similarity search using image embeddings. Accepts optional geo-location filter for search by latitude, longitude and optional distance radius. Images taken with GPS enabled are searchable by geo-location. Also accepts optional recency filter (defaults to null, meaning all time), and optional feed and collection identifiers to filter images by. Returns the matching images, including their content resource URI to retrieve the complete Markdown text.
extractText
Extracts JSON data from text using LLM. Accepts text to be extracted, and JSON schema which describes the data which will be extracted. JSON schema needs be of type 'object' and include 'properties' and 'required' fields. Optionally accepts text prompt which is provided to LLM to guide data extraction. Defaults to 'Extract data using the tools provided'. Returns extracted JSON from text.
createCollection
Create a collection. Accepts a collection name, and optional list of content identifiers to add to collection. Returns the collection identifier
addContentsToCollection
Add contents to a collection. Accepts a collection identifier and a list of content identifiers to add to collection. Returns the collection identifier.
removeContentsFromCollection
Remove contents from collection. Accepts a collection identifier and a list of content identifiers to remove from collection. Returns the collection identifier.
deleteContent
Deletes content from Graphlit knowledge base. Accepts content identifier. Returns the content identifier and content state, i.e. Deleted.
deleteCollection
Deletes collection from Graphlit knowledge base. Does *not* delete the contents in the collection, only the collection itself. Accepts collection identifier. Returns the collection identifier and collection state, i.e. Deleted.
deleteFeed
Deletes feed from Graphlit knowledge base. *Does* delete the contents in the feed, in addition to the feed itself. Accepts feed identifier. Returns the feed identifier and feed state, i.e. Deleted.
deleteFeeds
Deletes feeds from Graphlit knowledge base. *Does* delete the contents in the feed, in addition to the feed itself. Accepts optional feed type filter to limit the feeds which will be deleted. Also accepts optional limit of how many feeds to delete, defaults to 100. Returns the feed identifiers and feed state, i.e. Deleted.
deleteCollections
Deletes collections from Graphlit knowledge base. Does *not* delete the contents in the collections, only the collections themselves. Accepts optional limit of how many collections to delete, defaults to 100. Returns the collection identifiers and collection state, i.e. Deleted.
deleteContents
Deletes contents from Graphlit knowledge base. Accepts optional content type and file type filters to limit the contents which will be deleted. Also accepts optional limit of how many contents to delete, defaults to 1000. Returns the content identifiers and content state, i.e. Deleted.
queryContents
Query contents from Graphlit knowledge base. Do *not* use for retrieving content by content identifier - retrieve content resource instead, with URI 'contents://{id}'. Accepts optional content name, content type and file type for metadata filtering. Accepts optional recency filter (defaults to null, meaning all time), and optional feed and collection identifiers to filter images by. Accepts optional geo-location filter for search by latitude, longitude and optional distance radius. Images and videos taken with GPS enabled are searchable by geo-location. Returns the matching contents, including their content resource URI to retrieve the complete Markdown text.
queryCollections
Query collections from Graphlit knowledge base. Do *not* use for retrieving collection by collection identifier - retrieve collection resource instead, with URI 'collections://{id}'. Accepts optional collection name for metadata filtering. Returns the matching collections, including their collection resource URI to retrieve the collection contents.
queryFeeds
Query feeds from Graphlit knowledge base. Do *not* use for retrieving feed by feed identifier - retrieve feed resource instead, with URI 'feeds://{id}'. Accepts optional feed name and feed type for metadata filtering. Returns the matching feeds, including their feed resource URI to retrieve the feed contents.
isContentDone
Check if content has completed asynchronous ingestion. Accepts a content identifier which was returned from one of the non-feed ingestion tools, like ingestUrl. Returns whether the content is done or not.
isFeedDone
Check if an asynchronous feed has completed ingesting all the available content. Accepts a feed identifier which was returned from one of the ingestion tools, like ingestGoogleDriveFiles. Returns whether the feed is done or not.
listNotionDatabases
Lists available Notion databases. Returns a list of Notion databases, where the database identifier can be used with ingestNotionPages to ingest pages into Graphlit knowledge base.
listLinearProjects
Lists available Linear projects. Returns a list of Linear projects, where the project name can be used with ingestLinearIssues to ingest issues into Graphlit knowledge base.
listSlackChannels
Lists available Slack channels. Returns a list of Slack channels, where the channel name can be used with ingestSlackMessages to ingest messages into Graphlit knowledge base.
listSharePointLibraries
Lists available SharePoint libraries. Returns a list of SharePoint libraries, where the selected libraryId can be used with listSharePointFolders to enumerate SharePoint folders in a library.
listSharePointFolders
Lists available SharePoint folders. Returns a list of SharePoint folders, which can be used with ingestSharePointFiles to ingest files into Graphlit knowledge base.
ingestSharePointFiles
Ingests files from SharePoint library into Graphlit knowledge base. Accepts a SharePoint libraryId and an optional folderId to ingest files from a specific SharePoint folder. Libraries can be enumerated with listSharePointLibraries and library folders with listSharePointFolders. Accepts an optional read limit for the number of files to ingest. Executes asynchronously and returns the feed identifier.
ingestOneDriveFiles
Ingests files from OneDrive folder into Graphlit knowledge base. Accepts an optional read limit for the number of files to ingest. Executes asynchronously and returns the feed identifier.
ingestGoogleDriveFiles
Ingests files from Google Drive folder into Graphlit knowledge base. Accepts an optional read limit for the number of files to ingest. Executes asynchronously and returns the feed identifier.
ingestDropboxFiles
Ingests files from Dropbox folder into Graphlit knowledge base. Accepts optional relative path to Dropbox folder (i.e. /Pictures), and an optional read limit for the number of files to ingest. If no path provided, ingests files from root Dropbox folder. Executes asynchronously and returns the feed identifier.
ingestBoxFiles
Ingests files from Box folder into Graphlit knowledge base. Accepts optional Box folder identifier, and an optional read limit for the number of files to ingest. If no folder identifier provided, ingests files from root Box folder (i.e. "0"). Folder identifier can be inferred from Box URL. https://app.box.com/folder/123456 -> folder identifier is "123456". Executes asynchronously and returns the feed identifier.
ingestGitHubFiles
Ingests files from GitHub repository into Graphlit knowledge base. Accepts GitHub repository owner and repository name and an optional read limit for the number of files to ingest. For example, for GitHub repository (https://github.com/openai/tiktoken), 'openai' is the repository owner, and 'tiktoken' is the repository name. Executes asynchronously and returns the feed identifier.
ingestNotionPages
Ingests pages from Notion database into Graphlit knowledge base. Accepts Notion database identifier and an optional read limit for the number of pages to ingest. You can list the available Notion database identifiers with listNotionDatabases. Or, for a Notion URL, https://www.notion.so/Example/Engineering-Wiki-114abc10cb38487e91ec906fc6c6f350, 'Engineering-Wiki-114abc10cb38487e91ec906fc6c6f350' is an example of a Notion database identifier. Executes asynchronously and returns the feed identifier.
ingestMicrosoftTeamsMessages
Ingests messages from Microsoft Teams channel into Graphlit knowledge base. Accepts Microsoft Teams team identifier and channel identifier, and an optional read limit for the number of messages to ingest. Executes asynchronously and returns the feed identifier.
ingestSlackMessages
Ingests messages from Slack channel into Graphlit knowledge base. Accepts Slack channel name and an optional read limit for the number of messages to ingest. Executes asynchronously and returns the feed identifier.
ingestDiscordMessages
Ingests messages from Discord channel into Graphlit knowledge base. Accepts Discord channel name and an optional read limit for the number of messages to ingest. Executes asynchronously and returns the feed identifier.
ingestTwitterPosts
Ingests posts by user from Twitter/X into Graphlit knowledge base. Accepts Twitter/X user name, without the leading @ symbol, and an optional read limit for the number of posts to ingest. Executes asynchronously and returns the feed identifier.
ingestTwitterSearch
Searches for recent posts from Twitter/X, and ingests them into Graphlit knowledge base. Accepts search query, and an optional read limit for the number of posts to ingest. Executes asynchronously and returns the feed identifier.
ingestRedditPosts
Ingests posts from Reddit subreddit into Graphlit knowledge base. Accepts a subreddit name and an optional read limit for the number of posts to ingest. Executes asynchronously and returns the feed identifier.
ingestGoogleEmail
Ingests emails from Google Email account into Graphlit knowledge base. Accepts an optional read limit for the number of emails to ingest. Executes asynchronously and returns the feed identifier.
ingestMicrosoftEmail
Ingests emails from Microsoft Email account into Graphlit knowledge base. Accepts an optional read limit for the number of emails to ingest. Executes asynchronously and returns the feed identifier.
ingestLinearIssues
Ingests issues from Linear project into Graphlit knowledge base. Accepts Linear project name and an optional read limit for the number of issues to ingest. Executes asynchronously and returns the feed identifier.
ingestGitHubIssues
Ingests issues from GitHub repository into Graphlit knowledge base. Accepts GitHub repository owner and repository name and an optional read limit for the number of issues to ingest. For example, for GitHub repository (https://github.com/openai/tiktoken), 'openai' is the repository owner, and 'tiktoken' is the repository name. Executes asynchronously and returns the feed identifier.
ingestJiraIssues
Ingests issues from Atlassian Jira repository into Graphlit knowledge base. Accepts Atlassian Jira server URL and project name, and an optional read limit for the number of issues to ingest. Executes asynchronously and returns the feed identifier.
webCrawl
Crawls web pages from web site into Graphlit knowledge base. Accepts a URL and an optional read limit for the number of pages to crawl. Uses sitemap.xml to discover pages to be crawled from website. Executes asynchronously and returns the feed identifier.
webMap
Enumerates the web pages at or beneath the provided URL using web sitemap. Does *not* ingest web pages into Graphlit knowledge base. Accepts web site URL as string. Returns list of mapped URIs from web site.
webSearch
Performs web or podcast search based on search query. Can search for web pages or podcasts/podcast episodes. Format the search query as what would be entered into a Google search. You can use site filtering in the search query, like 'site:twitter.com'. Accepts search query as string, and optional search service type. Prefer calling this tool over using 'curl' directly for any web search. *Only* use Podscan search service type to search for podcasts or podcast episodes. Does *not* ingest pages into Graphlit knowledge base. *Does* ingest podcast episodes as transcribed audio files into Graphlit knowledge base. When searching for podcasts or podcast episodes, *don't* include the term 'podcast' or 'episode' in the search query - that would be redundant. Search service types: Tavily (web pages), Exa (web pages) and Podscan (podcast episodes). Defaults to Exa. Returns URL, title and relevant Markdown text from resulting web pages or podcast episode transcripts.
ingestRSS
Ingests posts from RSS feed into Graphlit knowledge base. For podcast RSS feeds, audio will be downloaded, transcribed and ingested into Graphlit knowledge base. Accepts RSS URL and an optional read limit for the number of posts to read. Executes asynchronously and returns the feed identifier.
ingestUrl
Ingests content from URL into Graphlit knowledge base. Can scrape web pages, and can ingest individual Word documents, PDFs, audio recordings, videos, images, or any other unstructured data. Executes asynchronously and returns the content identifier.
ingestText
Ingests text as content into Graphlit knowledge base. Accepts a name for the content object, the text itself, and an optional text type (Plain, Markdown, Html). Defaults to Markdown text type. Optionally accepts an identifier for an existing content object. Will overwrite existing content, if provided. Can use for storing long-term textual memories or the output from LLM or other tools as content resources, which can be later searched or retrieved. Executes *synchronously* and returns the content identifier.
ingestFile
Ingests local file into Graphlit knowledge base. Accepts the path to the file in the local filesystem. Can use for storing *large* long-term textual memories or the output from LLM or other tools as content resources, which can be later searched or retrieved. Executes asynchronously and returns the content identifier.
screenshotPage
Screenshots web page from URL. Executes *synchronously* and returns the content identifier.
describeImageUrl
Prompts vision LLM and returns completion. Does *not* ingest image into Graphlit knowledge base. Accepts image URL as string. Returns Markdown text from LLM completion.
describeImageContent
Prompts vision LLM and returns description of image content. Accepts content identifier as string, and optional prompt for image description. Returns Markdown text from LLM completion.
publishAudio
Publishes text as audio format, and ingests into Graphlit knowledge base. Accepts a name for the content object, the text itself, and an optional text type (Plain, Markdown, Html). Defaults to Markdown text type. Optionally accepts an ElevenLabs voice identifier. You *must* retrieve the content resource to get the downloadable audio URL for this published audio. Executes *synchronously* and returns the content identifier.
sendWebHookNotification
Sends a webhook notification to the provided URL. Accepts the webhook URL. Also accepts the text to be sent with the webhook, and an optional text type (Plain, Markdown, Html). Defaults to Markdown text type. Returns true if the notification was successfully sent, or false otherwise.
sendSlackNotification
Sends a Slack notification to the provided Slack channel. Accepts the Slack channel name. Also accepts the text for the Slack message, and an optional text type (Plain, Markdown, Html). Defaults to Markdown text type. Hint: In Slack Markdown, images are displayed by simply putting the URL in angle brackets like <https://example.com/image.jpg> instead of using the traditional Markdown image syntax ![alt text](url). Returns true if the notification was successfully sent, or false otherwise.
sendTwitterNotification
Posts a tweet from the configured user account. Accepts the plain text for the tweet. Tweet text rules: allowed - plain text, @mentions, #hashtags, URLs (auto-shortened), line breaks ( ). Not allowed - markdown, HTML tags, rich text, or custom styles. Returns true if the notification was successfully sent, or false otherwise.
sendEmailNotification
Sends an email notification to the provided email address(es). Accepts the email subject and a list of email 'to' addresses. Email addresses should be in RFC 5322 format. i.e. Alice Wonderland <[email protected]>, or [email protected] Also accepts the text for the email, and an optional text type (Plain, Markdown, Html). Defaults to Markdown text type. Returns true if the notification was successfully sent, or false otherwise.

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