Percy MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Percy through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"percy": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Percy, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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 Percy MCP Server
Inject precision quality assurance workflows directly bounding LLM models via the Percy Visual Testing API (by BrowserStack). Programmatically verify pixel regressions executing queries evaluating visual boundaries natively across target projects. Inspect deep status arrays parsing CI build limits dynamically, extract metrics evaluating granular snapshot checkpoints asynchronously, and force immediate test baseline approvals seamlessly directly from explicit prompt commands naturally.
LangChain's ecosystem of 500+ components combines seamlessly with Percy through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Project Navigation — Read bounded parameters tracking Percy deployments isolating configurations determining explicitly specific active QA targets natively
- Automated Build Oversight — Track specific arrays extracting dynamic checks returning pipeline checkpoints (approved/failed/unreviewed limits) explicitly seamlessly
- Visual Snapshot Operations — Log natively extracting bounds verifying comparison properties logging rendering differences mapping exact explicit width constraints
- Baseline Affirmations — Mutate bounding loops forcing active execution of JSON logic structurally bypassing native clicks allowing test approvals implicitly (
approve_buildorapprove_snapshot)
The Percy MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain 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 Percy to LangChain via MCP
Follow these steps to integrate the Percy MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from Percy via MCP
Why Use LangChain with the Percy MCP Server
LangChain provides unique advantages when paired with Percy through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Percy MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Percy queries for multi-turn workflows
Percy + LangChain Use Cases
Practical scenarios where LangChain combined with the Percy MCP Server delivers measurable value.
RAG with live data: combine Percy tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Percy, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Percy tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Percy tool call, measure latency, and optimize your agent's performance
Percy MCP Tools for LangChain (10)
These 10 tools become available when you connect Percy to LangChain via MCP:
approve_build
/approve` moving the test suite to green. Approve all unreviewed snapshots in a Percy build. Marks the entire build as visually approved for deployment
approve_snapshot
Approve a single Percy snapshot. Marks it as visually correct, updating the baseline for future comparisons
get_build_details
Get full details of a Percy build including state, total/unreviewed snapshot counts, approved/rejected snapshots, branch, commit SHA, and finalized timestamp
get_project_details
Get full details of a Percy project including name, slug, default branch, auto-approve enabled, browser targets, and build count
get_snapshot_details
Get full details of a Percy snapshot including name, review state, widths, fingerprint, and comparison count
list_browsers
List all supported browser families on Percy. Returns browser names, versions, and OS combinations for cross-browser visual testing
list_builds
List builds for a Percy project. Each build contains snapshots from a test run. Returns build IDs, states (processing/finished/failed), branch names, commit SHAs, and snapshot counts
list_comparisons
List visual comparisons for a Percy snapshot. Each comparison shows the diff between baseline and head at a specific width/browser. Returns diff images, diff percentages, and browser info
list_projects
List all projects on Percy (BrowserStack). Percy is the leading visual regression testing platform that captures snapshots and detects pixel-level UI differences across builds. Uses JSON:API format. Returns project names, slugs, and browser configs
list_snapshots
List snapshots in a Percy build. Each snapshot is a captured page/component at specific widths and browsers. Returns snapshot names, review states (unreviewed/approved/rejected), and diff percentages
Example Prompts for Percy in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Percy immediately.
"Log explicitly the builds targeting structural limits seamlessly isolating project 'org-slug/my-app' dynamically checking bounding states natively."
"Reverse check explicit structures extracting limits comparing properties cleanly bounding snapshot ID 'snap_778' natively efficiently."
"Force explicit validation mutating boundaries executing structurally an approval across build ID '8910' automatically natively flawlessly securely."
Troubleshooting Percy MCP Server with LangChain
Common issues when connecting Percy to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersPercy + LangChain FAQ
Common questions about integrating Percy MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Percy 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 Percy to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.