Reflect MCP. Map your knowledge graph with natural conversation.
Reflect lets your AI agent read, write, and explore your private knowledge graph directly through conversation. It turns your notes app into an active research assistant that maps connections between ideas, bookmarks, books, and daily thoughts.
Give Claude and any AI agent real-world access
The agent can show you every separate area or 'graph' where you keep notes.
You can ask the agent to pull up a note by title, list all notes in a workspace, or retrieve the full content of a single document.
The agent can create brand-new, structured notes and save them into your graph instantly.
You can append conversation summaries or quick ideas directly to today's date entry without creating a new note.
The agent finds all other notes that point back to a specific topic, revealing connections you might have forgotten about.
It saves web bookmarks or imports highlights from your reading list so they are searchable alongside your text notes.
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What AI agents can do with Reflect Notes: 10 Available Tools
These tools allow your AI agent granular control over every aspect of your personal knowledge base—from listing graphs to appending daily thoughts.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Reflect MCPAppend Daily Note
Adds formatted text content directly into today's date entry in your journal.
Create Link
Saves a new web link or bookmark to one of your defined knowledge graphs...
Create Note
Generates an entirely new note within a graph, allowing you to specify the subject...
Get Backlinks
Retrieves a list of all other notes that contain links pointing back to a specific...
Get Current User
Fetches basic profile details for the Reflect user who is logged into your AI client.
Get Note
Pulls up the full text and metadata for a specific, existing note in your graph.
List Books
Displays all books you have saved or imported into the Reflect system.
List Graphs
Shows a list of every separate workspace or 'graph' you currently use in Reflect...
List Links
Lists all the web bookmarks you have saved within a specific knowledge graph.
List Notes
Generates a list of every note contained within one designated Reflect graph.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Reflect, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Reflect Notes. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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The struggle of keeping track of your own brain
Right now, knowledge lives in silos. You have a research note here, a highlight list there, meeting minutes in another app, and key ideas scattered across multiple documents. To build one cohesive argument, you're constantly switching tabs, copying bullet points into a master document, and cross-referencing data manually. It’s exhausting, slow, and always feels like you're forgetting that critical link between two seemingly unrelated topics.
With this MCP, the process becomes conversational. You simply ask your agent, 'What connections exist between my notes on AI Ethics and my bookmarks from last month?' The system pulls together information using tools like `get_backlinks` and presents a synthesized answer, not just a list of documents. It turns fragmented data into immediate insight.
Reflect Notes: Structured Knowledge Capture
Manual logging means you either forget to log the decision entirely, or you write it down in a generic text file that has no connection to the project. You lose the metadata—the context of *when* and *why* that decision was made.
Now, by using tools like `append_daily_note` or `create_note`, your knowledge is automatically anchored to its date, its graph, and its subject matter. Your captured insights become part of a living record, not just ephemeral text.
What Reflect MCP does for your AI
You connect your Reflect account to your AI client to give it access to your personal, networked thought graph. This MCP lets you treat your entire collection of notes not as separate files, but as one interconnected web of knowledge.
Instead of manually searching through dozens of folders or apps, you simply ask your agent questions about your ideas. It can look up specific notes, find every piece of content that links back to a core concept, and map out the relationships between disparate thoughts. You can also tell it to capture action items from a call and log them directly into today’s daily note, or save a URL you just read so it gets indexed with metadata.
This integration means your AI agent becomes a personal knowledge broker that understands your context—the connections between your research, your reading list, and your brainstorming sessions. When you pair this MCP with the Vinkius catalog of tools, you build an assistant capable of synthesizing complex ideas without ever needing to leave your chat window.
019d75fe-08aa-71cd-bd2f-ed8415f79544 How to set up Reflect MCP
The bottom line is that you tell the AI what to find or write using plain English, and it handles the complex data retrieval from your private graph.
First, you authorize the Reflect MCP plugin within your active AI client extension.
Next, you secure your personal OAuth Access Token from your Reflect developer settings and embed it into the integration setup.
After connecting, you chat naturally with your agent, prompting tasks like, 'Find all notes connected to 'AI Strategy'.' or 'Summarize this meeting and log it to my daily note.'
Who uses Reflect MCP
This MCP is for anyone whose work relies on synthesizing information from multiple sources—the researcher who manages dozens of notes, the writer building an argument over months, or the consultant who needs to recall context from a project that happened last quarter.
You use this MCP to track connections between sources and theories. You ask your agent to run get_backlinks on key concepts, instantly seeing every paper or note where that idea has been mentioned.
You rely on the agent to pull together decisions from multiple meetings and articles. You ask it to compile a new document using create_note with structured data gathered from your graph.
When wrapping up a project, you prompt the agent to review all associated materials by listing related links and documents. You use append_daily_note to log key decisions for client reports.
Benefits of connecting Reflect MCP
Deep context retrieval: Instead of manually searching through dozens of files, just ask the agent to use get_backlinks and instantly see every note that referenced a key idea. It finds connections you might have forgotten about.
Structured logging: When you finish a call or meeting, tell your AI client to summarize it and log those decisions using append_daily_note. This keeps your main journal clean while ensuring no action item is lost.
Idea capture on the fly: Stop wasting time switching apps. You can ask the agent to create permanent notes with create_note or save a URL with create_link, keeping your brainstorming session uninterrupted.
Full knowledge visibility: Get an overview of all your work by first running list_graphs. This helps you understand which major workspaces contain related projects and ideas, making your entire system visible to the AI.
Reference material access: Your agent can handle external context. It shows you everything in list_books or pulls up a specific document using get_note, treating all your sources as equally accessible.
Reflect MCP use cases
Synthesizing research for a grant proposal
A researcher has compiled notes on five different theories. They ask their agent to run list_notes across the project graph, then use get_backlinks on 'Quantum Computing' to pull together every piece of evidence related to that topic, creating a comprehensive draft outline.
Archiving client meeting takeaways
A consultant finishes a video call. Instead of copying bullet points into an email, they tell their agent to summarize the discussion and use append_daily_note in the main project graph. This permanently logs the decisions with context.
Reviewing old work for inspiration
A writer is starting a new book chapter. They ask their agent to list all notes related to 'Victorian London' using list_notes. The AI then pulls up key details from an archived note with get_note, providing immediate context.
Building a project roadmap
A founder needs to track external inspiration. They use the agent to save crucial industry articles via create_link and then ask for a summary of all saved links related to 'AI Ethics', ensuring they capture ideas from multiple sources.
Reflect MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Using notes as simple dumping grounds
Pasting huge blocks of text into random documents without linking them, making the information hard to find later.
Don't just dump data. If it’s a core idea, use create_note and give it a clear subject. To connect it to existing work, always ask your agent to run get_backlinks on that new note.
Treating the graph like a simple file cabinet
Assuming that just listing notes (list_notes) is enough; failing to use the connections between them.
Don't stop at the list. After running list_notes, tell your agent, 'Now find all the backlinks for the top three items.' This reveals the true context of your knowledge.
Losing track of quick insights
Having brilliant ideas during a meeting but having to manually copy them into an external document later.
Keep it in Reflect. Immediately use append_daily_note or create_note while the idea is fresh. This guarantees the context and date are logged automatically.
When to use Reflect MCP
Use this MCP if your core job involves synthesis, relationship mapping, or recall from a large, interconnected body of work. You need to know how ideas connect—not just that they exist. The value here is in the 'backlinks' capability; it solves the problem of knowing what you already know about a topic. Don't use this if your primary task is simple data logging (like a CRM or calendar) or structured transaction processing, as those tools manage discrete records better. If all you need to do is save a single list of names and emails, a dedicated contact manager works fine. But if you need the AI to look at 10 different notes and tell you what three common themes they share, this MCP is essential.
Frequently asked questions about Reflect MCP
How does Reflect MCP help me find connections between my notes? +
It uses the get_backlinks tool to scan your entire graph and list every single note that points back to a specific concept. This reveals context you might have otherwise missed.
Can Reflect MCP write new content for me? +
Yes, it can create entirely new notes using create_note or append structured updates to your journal via append_daily_note. You just give the agent the material and tell it where to put it.
Do I need a specific client app to use Reflect MCP? +
No, as long as your AI client supports the Model Context Protocol (MCP) standard, you can connect this integration. This means compatibility across most modern agents and coding environments.
What is the difference between `list_notes` and `get_note` in Reflect MCP? +
list_notes gives you a directory of every note in a graph, showing titles. get_note pulls up the actual content and metadata for one specific note when you know its title or ID.
How do I save external information using Reflect MCP? +
You use the create_link tool to bookmark URLs. The agent handles extracting relevant metadata automatically, so your bookmarks are searchable alongside everything else in your graph.