Capacities MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Capacities 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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Vinkius supports streamable HTTP and SSE.
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 Capacities. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Capacities?"
)
print(response)
asyncio.run(main())
* 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
About Capacities MCP Server
Connect your Capacities account to any AI agent and take full control of your object-based personal knowledge management through natural conversation.
LlamaIndex agents combine Capacities tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Spaces & Structures — Enumerate your personal spaces and discover the exact object type structures mapping your active environment.
- Object Instantiation — Build new typed graph objects complying precisely with the predefined structure parameters.
- Daily Note Appends — Send quick thoughts, summaries, and Markdown text directly into your mapped daily note log.
- Content Lookups — Execute rapid keyword searches targeting explicit object hierarchies to track down active nodes.
- Rich Link Saving — Parse and inject web URLs dynamically into your space as Weblink objects, triggering automatic previews.
- Media & Tagging — Attach images and add tags to existing objects to organize your graph relations instantly.
The Capacities MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Capacities to LlamaIndex via MCP
Follow these steps to integrate the Capacities MCP Server with LlamaIndex.
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 10 tools from Capacities
Why Use LlamaIndex with the Capacities MCP Server
LlamaIndex provides unique advantages when paired with Capacities through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Capacities tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Capacities tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Capacities, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Capacities tools were called, what data was returned, and how it influenced the final answer
Capacities + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Capacities MCP Server delivers measurable value.
Hybrid search: combine Capacities real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Capacities 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 Capacities for fresh data
Analytical workflows: chain Capacities queries with LlamaIndex's data connectors to build multi-source analytical reports
Capacities MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Capacities to LlamaIndex via MCP:
add_tag
Add a structural categorical Tag linking explicitly dynamically grouping related Graph items via relations
create_object
Create a new typed object in a Capacities space bounded by specific graph rules instantiating entities
get_object
Retrieve a specific full explicit object by ID accessing its root graph data traversing properties internally
get_space_info
Retrieve detailed information about a Capacities space including all object types (structures), their property definitions, and configuration
get_structures
Get all object type definitions (structures) within a Capacities space exposing exact metadata parameters limitlessly
list_spaces
List all personal spaces in the Capacities account. Spaces are top-level containers for organizing objects, notes, and knowledge
lookup
Search for content across a specific Capacities space by title or explicit keywords tracking exact nodes
save_media
Locate and attach an explicit Media payload explicitly binding it directly onto existing specific record scopes
save_to_daily_note
Append strict Markdown textual payloads to the dynamically mapped daily note explicitly linking content blocks
save_weblink
Save a web URL as a Weblink object dynamically tracking automatic preview generation natively
Example Prompts for Capacities in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Capacities immediately.
"Search my 'Work' space for the product launch meeting notes and summarize them."
"Save this URL https://example.com to my 'Research' space as a new Weblink."
"Append the code I just wrote to my daily note to remember the bugfix."
Troubleshooting Capacities MCP Server with LlamaIndex
Common issues when connecting Capacities to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCapacities + LlamaIndex FAQ
Common questions about integrating Capacities MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Capacities with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Capacities to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.