Fibery MCP. Query, update, and manage work records via conversation.
Fibery MCP connects your entire work management workspace to your AI agent. It lets you read schemas, query data across all custom databases, create new tasks, and add status updates—all through natural conversation. Stop navigating menus; start asking questions about your project data.
Give Claude and any AI agent real-world access
Retrieve a map of all your apps, databases, and custom fields so the agent knows where to look.
Pull details for any single item (entity) using its unique ID or by searching keywords across multiple databases.
Create, modify, or delete entire records in custom databases based on your instructions.
Read the conversation history or add a new comment to any project record.
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What AI agents can do with Fibery: 11 Tools for Enterprise Automation
These tools allow your AI agent to perform granular actions across every part of your Fibery workspace, from listing users to running advanced database queries.
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 Fibery MCPAdd Comment
Posts a new comment onto an existing project record (entity).
Create Entity
Builds and saves a brand-new item into any specified database.
Delete Entity
Permanently removes an existing project record (entity).
Get Comments
Retrieves all comments posted to a specific record, letting you see the full history.
Get Entity
Fetches all data for one specific item using its unique ID.
Get Schema
Retrieves a blueprint of your entire workspace, showing every available database and field type.
List Apps
Lists all the main functional areas (spaces) used in your Fibery account.
List Users
Shows a list of every user who has access to your workspace.
Query Entities
Searches and pulls data from specific databases using detailed filters you provide.
Search Entities
Looks for information across every single database in your workspace using keywords.
Update Entity
Changes the data (like status or assignee) on an existing record.
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 Fibery, 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 Fibery. 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.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The Pain of Manual Data Collection
Today, gathering a full project status report means opening the main work management platform. You then have to click into the 'Product' tab, check its key metrics. Next, you switch over to the 'Software' tab and run a separate query for bug counts. Then you might need to open an unrelated 'Marketing' space just to see who is assigned to review it. This process takes 15 minutes of clicking, copying names, and pasting into a summary spreadsheet.
With this MCP, your agent handles the entire sequence in seconds. You tell it: 'Pull the status metrics for Product, Software, and Marketing, and list any outstanding action items.' The agent uses multiple tools—like `query_entities` across different spaces—and gives you one coherent, ready-to-read answer.
Accessing Records with Fibery MCP
The tedious steps that vanish are the context switches and manual data pulls. You no longer have to ask a team member, 'What's the status of X?' Instead, your agent runs `get_entity` using the specific ID, providing you with the current details instantly.
It’s not about automating clicks; it’s about eliminating context loss entirely. Everything—the data, the comments, the history—is available in one conversational flow.
What Fibery MCP does for your AI
This MCP gives your agent direct access to the heart of your Fibery workspace. You don't have to jump into the portal and click around just to find a piece of information or update a status. Instead, you talk to your AI client, and it handles the complex database interactions for you.
Need to know what’s going on with Product X? Your agent can pull structured data from specific databases, search across every app in your workspace, and even tell you exactly who needs to review something by listing all users. You can ask your agent to update a task status or add a comment directly to an entity record without ever leaving your chat window.
If you're looking for robust ways to handle custom workflows from different clients, Vinkius hosts this MCP, ensuring deep compatibility with any AI agent.
This means software teams can sync development progress and product managers can gather insights simply by asking questions in plain English.
019d7598-7881-701b-93f4-378efe8cc1ab How to set up Fibery MCP
The bottom line is, once connected, your AI agent treats Fibery like a single data source you can talk to.
Subscribe to this MCP and provide your Fibery workspace name along with an API token.
Connect your preferred AI client (like Claude, Cursor, or Windsurf) through the Vinkius catalog.
Instruct your agent on what you need—for example, 'Find all tasks assigned to me in Marketing Operations that haven't been updated this week.'
Who uses Fibery MCP
Product Managers and Operations staff who spend too much time switching between the project management tool and their chat window. It's for anyone whose job involves querying complex, interconnected business data stored in custom databases.
Gathering status updates or finding all related tasks across different product spaces without having to manually navigate the portal.
Running complex data checks, like verifying if a required field is populated before closing out an account record, and logging that confirmation in a central task.
Pulling specific entity details about bug reports or feature requests to update the sprint board status directly from their chat environment.
Benefits of connecting Fibery MCP
Stop navigating menus. Instead of opening multiple tabs to gather data from different project spaces, you simply ask your agent for the information. The agent handles the cross-database lookup automatically.
You can automate status changes instantly. If a bug is fixed and ready for QA, tell your agent instead of finding the card, clicking 'Status,' and selecting 'Ready.' Use update_entity to change it directly.
Keep team context alive. Need to know what was decided last week? Your agent can use get_comments to pull the conversation history attached to any record, so you never lose critical decisions in a thread.
Build custom reporting without SQL. Instead of exporting data and running joins in a spreadsheet, use query_entities to pull exactly the structured data set you need and get it back immediately for analysis.
Centralize knowledge. If you're unsure which databases exist or what fields they hold, let your agent run get_schema. It gives you a full map of everything available in your workspace.
Fibery MCP use cases
The QA Team needs to check all related tickets.
Instead of opening the 'Software Development' space and manually cross-referencing multiple databases for bug reports, the agent uses search_entities with keywords like 'API failure' across all spaces. It compiles a single list of affected records instantly.
The Product Manager needs to check user permissions.
The PM can ask their agent for a list of users and then specifically request details on who has access, using list_users to verify team membership before onboarding new contractors.
A developer finished the feature and needs to signal completion.
The dev doesn't need to click through multiple dropdown menus. They simply ask their agent to 'Mark this entity as complete and assign it to QA.' The agent runs update_entity using the appropriate record ID.
A stakeholder needs a summary of all active projects.
The agent can run list_apps first, giving the stakeholder an overview of all functional areas. Then, it uses query_entities to pull key metrics (like 'Last Updated Date' and 'Status') from each app into one readable report.
Fibery MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Trying to search unstructured documents.
You can't just ask the agent, 'Find me the PDF attachment about Q3 planning.' The MCP is designed for structured work data (entities), not file storage.
Changing a record without knowing its ID.
A user tries to say, 'Change the status of the bug report to Done.' The agent won't know which one; it needs a specific identifier to run update_entity.
Ignoring the schema map.
Assuming data exists in a field name like 'Client ID,' when the actual database uses 'Customer UUID.' Running query_entities with the wrong field name fails immediately.
When to use Fibery MCP
Use this MCP if your core workflow involves managing structured records, tracking status changes, or querying cross-functional data (e.g., linking a bug report to a product space and an assigned user). You need reliable actions like update_entity and the ability to run complex queries using filters.
Don't use it if your main goal is simple document archiving, managing external files, or communicating with systems that don't treat information as structured 'entities.' If you only need to read a static list of names, simply asking for list_users might suffice. This MCP shines when the data needs manipulation: creating records (create_entity), updating statuses (update_entity), or comparing data points across databases.
Frequently asked questions about Fibery MCP
How does Fibery MCP handle cross-database searches? +
The agent runs search_entities, which looks for keywords across every single database type (or 'app') in your workspace. It doesn't just check one area.
Can I use Fibery MCP to update an entity status? +
Yes, you can. Using update_entity, the agent changes any field on a record, such as moving a task from 'In Progress' to 'Review.' You just need the specific item ID.
What is the best way to get an overview of my workspace? +
Run list_apps first. This gives you a list of all major spaces, and then you can use get_schema for details on what data lives inside each one.
Does Fibery MCP only work with tasks? +
No, it works with any structured 'entity.' You're not limited to task management; you can manage custom databases—like lists of vendors or required equipment—too.