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shafi201104

Travel Assistant MCP Server

by shafi201104
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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)

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