Skip to main content
Glama
shafi201104

Travel Assistant MCP Server

by shafi201104
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

AI Agent Based Travel Assistant Claude API + MCP

What exists here

Piece

File

What it does

Sandbox data layer

src/tp_mcp/sandbox.py

Loads TravelPlanner queries, parses reference_information into per-city sections

MCP server

src/tp_mcp/server.py

Exposes the sandbox as MCP tools over stdio

Agent loop

src/agent/loop.py

Claude tool-use loop driving the MCP session

Prompts

src/agent/prompts.py

Versioned system prompts (planner, sole-planning, chat)

Plan schema

src/agent/schema.py

Pydantic contract matching the benchmark's plan format

Evaluator

src/eval/constraints.py

Commonsense + hard constraint checks, benchmark-style metrics

Batch runner

src/eval/run_eval.py

Runs N queries, writes traces + a metrics summary

UI

src/ui/app.py

Streamlit chat for participant testing

Tests

tests/test_constraints.py

9 offline tests, no API key needed

Setup (30 minutes)

python -m venv .venv
source .venv/bin/activate          # Windows cmd:  .venv\Scripts\activate
pip install -r requirements.txt

cp .env.example .env 
python scripts/prepare_data.py

pytest -q                          # 9 tests, no API calls
python scripts/check_setup.py      # key, dataset, MCP server, one API call

Then, first real run. Use run.py and everything works the same on every platform -- no PYTHONPATH to set:

python run.py eval.run_eval --mode sole-planning --n 5 --level easy   # cheap, ~1 min
python run.py agent.loop 0                    # one agentic run, prints the full trace
python run.py eval.run_eval --mode tool-use --n 5 --level easy
streamlit run src/ui/app.py

Architecture

  Streamlit UI ──┐
                 ├──► agent/loop.py ──── Anthropic Messages API (Claude)
  eval runner ───┘         │                      ▲
                           │  tool_use blocks     │  tool_result blocks
                           ▼                      │
                    MCP ClientSession ────────────┘
                           │  stdio (JSON-RPC)
                           ▼
                    tp_mcp/server.py  (FastMCP)
                           │
                           ▼
              TravelPlanner sandbox (reference_information / CSV database)

This server cannot be installed

F
license - not found
-
quality - not tested
C
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
–Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

  • MCP Server

    johnleider
    A
    license
    -
    quality
    D
    maintenance
    A Machine Context Protocol server that enables Claude AI to interact with tools through a structured communication interface, following standard MCP patterns with server initialization and stdio transport.
    1,299
    2
    MIT

  • Server MCP

    SeydinaBANE
    F
    license
    -
    quality
    D
    maintenance
    Provides math and weather tools accessible via LangGraph agent using MCP protocol with stdio and streamable HTTP transports.
    1

  • veriloop

    arvindcr4
    A
    license
    A
    quality
    C
    maintenance
    Exposes a verified tool registry (calculator, sandboxed file read, web fetch) over MCP stdio, enabling any MCP-capable client to reuse the same tools from the inspectable ReAct loop.
    3
    MIT

View all related MCP servers

Related MCP Connectors

  • Reasoning Commons

    AI Reasoning Cache & Consensus Layer with 11 MCP tools via Streamable HTTP.

  • microservices.sh

    MCP server for AI agents to plan, verify, and deploy Cloudflare-native apps.

  • clipkit

    MCP server for Clipkit — gives AI agents a video toolbox via the Clipkit schema.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/shafi201104/AI-Travel-Assistant-MCP-Arc'

If you have feedback or need assistance with the MCP directory API, please join our Discord server