Reclaim.ai 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 Reclaim.ai 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 Reclaim.ai. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Reclaim.ai?"
)
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 Reclaim.ai MCP Server
Connect your Reclaim.ai intelligent scheduling assistant directly to your AI agent. Enabling this integration turns your AI into an advanced executive assistant, capable of instantly scanning your schedule, managing priorities, and inserting new smart tasks into your Google Calendar effortlessly.
LlamaIndex agents combine Reclaim.ai 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
- Smart Task Management — Create, update, or delete dynamic tasks, adjusting their duration and priority while letting Reclaim handle the automated calendar placement.
- Habit Tracking — Review your recurring protected time blocks (Habits) scheduled to accommodate deep work, routines, and breaks.
- Calendar Review — List both manual and AI-scheduled events for specific date ranges to understand your true availability.
- Scheduling Links — Retrieve your shareable booking page URLs instantly to send to teammates or clients directly from chat.
- Time Analytics — Extract quantitative data tracking how you allocate focus across categories over customized ranges.
The Reclaim.ai 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 Reclaim.ai to LlamaIndex via MCP
Follow these steps to integrate the Reclaim.ai 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 Reclaim.ai
Why Use LlamaIndex with the Reclaim.ai MCP Server
LlamaIndex provides unique advantages when paired with Reclaim.ai through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Reclaim.ai tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Reclaim.ai tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Reclaim.ai, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Reclaim.ai tools were called, what data was returned, and how it influenced the final answer
Reclaim.ai + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Reclaim.ai MCP Server delivers measurable value.
Hybrid search: combine Reclaim.ai real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Reclaim.ai 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 Reclaim.ai for fresh data
Analytical workflows: chain Reclaim.ai queries with LlamaIndex's data connectors to build multi-source analytical reports
Reclaim.ai MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Reclaim.ai to LlamaIndex via MCP:
create_task
Specify title, duration in minutes, due date, and priority (P1 to P4). Creates a new task to be auto-scheduled by Reclaim.ai
delete_task
This action is irreversible. Deletes a task from Reclaim.ai
get_analytics
Retrieves time analytics for a specific date range
get_current_user
Retrieves the authenticated user profile
get_task
Retrieves details for a specific Reclaim.ai task
list_calendar_events
Lists all events on the Reclaim.ai planner for a date range
list_habits
Lists all habits configured in Reclaim.ai
list_scheduling_links
Lists all Reclaim.ai scheduling links
list_tasks
You can filter by status (NEW, SCHEDULED, IN_PROGRESS, COMPLETE). Lists all tasks managed by Reclaim.ai
update_task
Provide a JSON object with the updates. Updates an existing Reclaim.ai task
Example Prompts for Reclaim.ai in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Reclaim.ai immediately.
"Create a new task to draft the Q3 analytics report taking 3 hours with P1 priority."
"Delete task with ID 20392."
"Show my time spent analytics between 2024-01-01 and 2024-01-31."
Troubleshooting Reclaim.ai MCP Server with LlamaIndex
Common issues when connecting Reclaim.ai to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpReclaim.ai + LlamaIndex FAQ
Common questions about integrating Reclaim.ai 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 Reclaim.ai 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 Reclaim.ai to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.