Figshare MCP Server for LlamaIndexGive LlamaIndex instant access to 20 tools to Complete File Upload, Create Collection, Create Private Article, and more

Name: Figshare
Price: 29 USD
Availability: InStock
Rating: 4.9 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Figshare as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The Figshare MCP Server for LlamaIndex is a standout in the Data Management category — giving your AI agent 20 tools to work with, ready to go from day one.

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Figshare. "
            "You have 20 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Figshare?"
    )
    print(response)

asyncio.run(main())

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About Figshare MCP Server

Connect your Figshare account to any AI agent to streamline your research data management and publication workflows through natural conversation.

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.

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.

The Figshare MCP Server exposes 20 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 20 Figshare tools available for LlamaIndex

When LlamaIndex connects to Figshare through Vinkius, your AI agent gets direct access to every tool listed below — spanning open-science, research-data, academic-publishing, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

complete

Complete file upload on Figshare

Complete a file upload

create

Create collection on Figshare

Create a new collection

create

Create private article on Figshare

Create a new private article

create

Create project on Figshare

Create a new project

delete

Delete article on Figshare

Delete an article

get

Get article on Figshare

Get details of a specific article

get

Get article downloads on Figshare

Get total downloads for an article

get

Get article views on Figshare

Get total views for an article

get

Get custom fields on Figshare

Get custom metadata fields for the institution

get

Get file details on Figshare

Get file details

get

Get hrfeed upload on Figshare

Get HR feed upload details

initiate

Initiate file upload on Figshare

Initiate a file upload for an article

list

List article files on Figshare

List files for an article

list

List public articles on Figshare

List public articles

list

List public collections on Figshare

List public collections

list

List public projects on Figshare

List public projects

Search articles on Figshare

Advanced search for articles

Search collections on Figshare

Advanced search for collections

Search projects on Figshare

Advanced search for projects

update

Update article on Figshare

Update an existing article

Connect Figshare to LlamaIndex via MCP

Follow these steps to wire Figshare into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 20 tools from Figshare

Why Use LlamaIndex with the Figshare MCP Server

LlamaIndex provides unique advantages when paired with Figshare through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Figshare tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Figshare tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Figshare, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Figshare tools were called, what data was returned, and how it influenced the final answer

Figshare + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Figshare MCP Server delivers measurable value.

Hybrid search: combine Figshare real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Figshare to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Figshare for fresh data

Analytical workflows: chain Figshare queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for Figshare in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Figshare immediately.

"List the most recent public articles on Figshare."

"Create a private article titled 'Lab Results Q4' with the description 'Raw data from the December experiments'."

"Show me all files attached to article 1234567."

Troubleshooting Figshare MCP Server with LlamaIndex

Common issues when connecting Figshare to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Figshare + LlamaIndex FAQ

Common questions about integrating Figshare MCP Server with LlamaIndex.

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.