Sally MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Add Comment, Check Sally Health, Create Project, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Sally as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Sally app connector for LlamaIndex is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Sally. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Sally?"
)
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 Sally MCP Server
Connect your Sally instance to any AI agent and take full control of your API-first project management through natural conversation.
LlamaIndex agents combine Sally tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Projects — Create, list, and inspect projects with full metadata.
- Tasks — Full CRUD with priorities (P1-P4), statuses, labels, and assignees.
- Comments — Add comments to any task for collaboration and status updates.
- Kanban Board — Retrieve the aggregated board view showing tasks organized by status columns.
- Timesheets — Access timesheet reports with tracked hours and billing information.
- Profile — Verify your authenticated identity and workspace permissions.
The Sally MCP Server exposes 12 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.
All 12 Sally tools available for LlamaIndex
When LlamaIndex connects to Sally through Vinkius, your AI agent gets direct access to every tool listed below — spanning task-management, kanban, api-first, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Comments are visible to all project members. Add a comment to a task
Check Sally instance health
Create a new project
Optionally set priority (P1-P4), status, and labels. Create a new task in a project
Get the Kanban board view
Get the authenticated user profile
Get details of a specific project
Get full details of a specific task
Get timesheet report for the workspace or project
List all projects in the workspace
Optionally filter by project ID to see tasks for a specific project. List tasks, optionally filtered by project
Only provided fields are changed. Update an existing task
Connect Sally to LlamaIndex via MCP
Follow these steps to wire Sally into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Sally MCP Server
LlamaIndex provides unique advantages when paired with Sally through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Sally tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Sally tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Sally, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Sally tools were called, what data was returned, and how it influenced the final answer
Sally + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Sally MCP Server delivers measurable value.
Hybrid search: combine Sally real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Sally 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 Sally for fresh data
Analytical workflows: chain Sally queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Sally in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Sally immediately.
"List all projects in my Sally workspace."
"Create a P2 task 'Implement auth middleware' in project proj_abc123 with labels 'backend, security'."
"Show me the Kanban board for project proj_abc123."
Troubleshooting Sally MCP Server with LlamaIndex
Common issues when connecting Sally to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpSally + LlamaIndex FAQ
Common questions about integrating Sally MCP Server with LlamaIndex.