Bring Open Science
to LlamaIndex
Learn how to connect Figshare to LlamaIndex and start using 20 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Figshare MCP Server?
Connect your Figshare account to any AI agent to streamline your research data management and publication workflows through natural conversation.
What you can do
- Article Management — List public articles, fetch specific article details, and create, update, or delete private articles in your account.
- File Handling — List files associated with articles, initiate multi-part S3 uploads, and track file details for your research datasets.
- Collections & Projects — Create and list public collections and projects to organize your scholarly output effectively.
- Metadata Control — Update titles, descriptions, and other metadata for your articles to ensure they are discoverable and well-documented.
How it works
- Subscribe to this server
- Enter your Figshare Personal Access Token
- Start managing your research repository from Claude, Cursor, or any MCP-compatible client
No more manual navigation through repository interfaces to check upload statuses or update metadata. Your AI acts as a research data manager.
Who is this for?
- Researchers & Academics — quickly upload datasets, update article descriptions, and check publication statuses without leaving your workspace.
- Data Managers — automate the organization of large collections and projects across institutional repositories.
- Librarians & Archivists — query public research outputs and manage metadata updates efficiently.
Built-in capabilities (20)
Complete a file upload
Create a new collection
Create a new private article
Create a new project
Delete an article
Get details of a specific article
Get total downloads for an article
Get total views for an article
Get custom metadata fields for the institution
Get file details
Get HR feed upload details
Initiate a file upload for an article
List files for an article
List public articles
List public collections
List public projects
Advanced search for articles
Advanced search for collections
Advanced search for projects
Update an existing article
Why LlamaIndex?
LlamaIndex agents combine Figshare tool responses with indexed documents for comprehensive, grounded answers. Connect 20 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine Figshare tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Figshare tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Figshare, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Figshare tools were called, what data was returned, and how it influenced the final answer
Figshare in LlamaIndex
Figshare and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Figshare to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Figshare in LlamaIndex
The Figshare MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 20 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Figshare for LlamaIndex
Every tool call from LlamaIndex to the Figshare MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I upload files to a Figshare article using this integration?
Yes. You can use initiate_file_upload to start the process and complete_file_upload once the data transfer is finished. You can also use list_article_files to verify the contents of any article.
How do I create a new private draft for my research?
Simply ask the agent to use the create_private_article tool. Provide a title and an optional description, and the agent will generate a new private entry in your Figshare account.
Is it possible to organize my articles into projects or collections?
Absolutely. You can use create_project or create_collection to set up organizational structures, and use list_public_projects or list_public_collections to browse existing ones.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query Figshare tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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