GetStream MCP Server for LlamaIndexGive LlamaIndex instant access to 23 tools to Add Activity To Feed, Add To Collection, Batch Delete Collections, and more
GDPR Free for SubscribersLlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add GetStream 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 MCP Server for LlamaIndex
The GetStream MCP Server for LlamaIndex is a standout in the Productivity category — giving your AI agent 23 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport 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 GetStream. "
"You have 23 tools available."
),
)
response = await agent.run(
"What tools are available in GetStream?"
)
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 GetStream MCP Server
Connect GetStream to your AI agent to orchestrate complex social architectures and activity feeds using natural language.
LlamaIndex agents combine GetStream tool responses with indexed documents for comprehensive, grounded answers. Connect 23 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
- Feed Management — Retrieve, add, or remove activities from specific feed slugs and user timelines using
get_feedandadd_activity_to_feed. - Activity Orchestration — Update activity metadata or perform partial updates to specific fields via
partial_update_activitywithout rewriting entire objects. - Social Graph — Manage follower relationships, list who follows a feed, and perform follow operations using
follow_feedandlist_feed_followers. - Collections & Files — Handle collection objects and manage file/image uploads for rich media experiences.
- Open Graph — Retrieve Open Graph data for URLs to enrich activity content automatically.
The GetStream MCP Server exposes 23 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 23 GetStream tools available for LlamaIndex
When LlamaIndex connects to GetStream through Vinkius, your AI agent gets direct access to every tool listed below — spanning activity-feeds, chat-api, social-infrastructure, 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.
Add activity to feed on GetStream
Add an activity to a feed
Add to collection on GetStream
Add objects to a collection
Batch delete collections on GetStream
Batch delete collections
Batch follow on GetStream
Batch follow multiple feeds
Batch get collections on GetStream
Batch retrieve collections
Batch post collections on GetStream
Batch create/update collections
Delete collection object on GetStream
Delete an individual collection object
Delete file on GetStream
Delete a file by URL
Follow feed on GetStream
Follow a target feed
Get activities on GetStream
Retrieve specific activities by ID or foreign ID
Get collection object on GetStream
Retrieve an individual collection object
Get feed on GetStream
Supports pagination. Retrieve activities in a feed
Get open graph on GetStream
Scrape Open Graph data from a URL
List feed followers on GetStream
List feeds following this feed
List feed follows on GetStream
List feeds this feed follows
Partial update activity on GetStream
Partially update activity data
Process image on GetStream
Process or resize an image
Remove activity from feed on GetStream
Remove an activity from a feed
Unfollow feed on GetStream
Unfollow a target feed
Update activities on GetStream
Update activity metadata
Update collection object on GetStream
Update an individual collection object
Upload file on GetStream
Upload a file
Upload image on GetStream
Upload an image
Connect GetStream to LlamaIndex via MCP
Follow these steps to wire GetStream into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind 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 GetStream MCP Server
LlamaIndex provides unique advantages when paired with GetStream through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine GetStream tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain GetStream tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query GetStream, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what GetStream tools were called, what data was returned, and how it influenced the final answer
GetStream + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the GetStream MCP Server delivers measurable value.
Hybrid search: combine GetStream real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query GetStream 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 GetStream for fresh data
Analytical workflows: chain GetStream queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for GetStream in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with GetStream immediately.
"Show me the latest activities in the 'user' feed for user ID 'user_123'."
"Make the feed 'timeline:alice' follow 'user:bob'."
"Update activity ID 'act_999' to set the 'is_featured' field to true."
Troubleshooting GetStream MCP Server with LlamaIndex
Common issues when connecting GetStream to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpGetStream + LlamaIndex FAQ
Common questions about integrating GetStream 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?
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