mcp-agent-toolkit

An MCP (Model Context Protocol) server exposing two other projects in this portfolio as tools any MCP client -- Claude Desktop, or any other MCP-compatible app -- can call directly:

• query_finance_filings -- hybrid RAG search (BM25 + semantic + cross-encoder reranking) with cited answers over 10 companies' real SEC 10-K filings, from rag-finance-assistant.
• fix_code_bug -- plans, writes, and test-verifies a fix for a seeded bug in a small demo repo, from code-fix-agent's bounded LangGraph loop.
• list_finance_companies -- lists the 10 available tickers.

MCP is the protocol OpenAI, Google DeepMind, and Microsoft have all adopted for connecting LLM clients to external tools -- this project is about proving I can package real, already-working agentic systems behind it, not a toy "hello world" server.

Why vendored, not a dependency on the sibling repos

vendor/rag_finance/ and vendor/code_fix_agent/ are copies of the relevant source (and, for the finance side, the already-cleaned SEC filing text) from the two sibling repos, not a pip install of them or a git submodule. A recruiter who clones this repo should get a working server without also having to clone and wire up two other repositories -- self-contained beats DRY for a single-purpose portfolio piece like this one. The tradeoff, stated plainly: a bug fixed in the original rag-finance-assistant or code-fix-agent repos won't automatically appear here.

Setup

python -m venv .venv
.venv\Scripts\activate   # source .venv/bin/activate on macOS/Linux
pip install -r requirements.txt

# One-time: build the local vector store for query_finance_filings.
# No API key needed -- embeddings are local sentence-transformers.
python scripts/build_finance_index.py

Create a .env file at the project root (gitignored) with your own key, only needed for query_finance_filings's generation step and for fix_code_bug:

ANTHROPIC_API_KEY=sk-ant-...

Connect it to Claude Desktop

Add this to Claude Desktop's claude_desktop_config.json (Settings -> Developer -> Edit Config):

{
  "mcpServers": {
    "ai-portfolio-toolkit": {
      "command": "C:\\path\\to\\mcp-agent-toolkit\\.venv\\Scripts\\python.exe",
      "args": ["C:\\path\\to\\mcp-agent-toolkit\\server.py"],
      "env": { "ANTHROPIC_API_KEY": "sk-ant-..." }
    }
  }
}

Restart Claude Desktop, then ask it something like "What did Apple's 10-K say about total net sales? Use the finance filings tool." -- Claude will call query_finance_filings itself and show the tool call in its UI.

Run the server directly (for debugging, not how an MCP client uses it)

python server.py

Speaks MCP over stdio -- not meant to be interacted with directly in a terminal; use an MCP client (Claude Desktop, or the mcp SDK's own dev inspector: mcp dev server.py) to actually call the tools.

Design choices, stated up front

• Environment-variable API key, not per-call config. The sibling Streamlit dashboards pass keys through per-request config because they're shared multi-tenant deployments -- one process, many visitors, each supplying their own key. An MCP server launched by Claude Desktop is the opposite shape: one process per user, started by their own client. An env var set in that user's own claude_desktop_config.json is the correct BYOK pattern here, not a shortcut.
• fix_code_bug never opens a PR. Unlike code-fix-agent's own dashboard, there's no natural place in a tool call for a visitor to supply their own GitHub token and target repo, and letting an LLM's tool-call decision push code somewhere is a meaningfully bigger blast radius than proposing a diff it can review first. Scoped to "propose and verify a fix" only -- see mcp_tools/code_fix.py.
• query_finance_filings doesn't modify the vendored retrieval.py. Company filtering happens by biasing the retrieval query with the company's full name and filtering the returned pool by ticker afterward, rather than adding a where filter to the vendored Chroma query -- keeps the vendored retrieval code byte-for-byte traceable back to its source project. See mcp_tools/finance_qa.py.
• Every fix_code_bug call gets a disposable copy of the demo repo. Same statefulness lesson as code-fix-agent's own dashboard: operating on the vendored original directly would mean the first call's "fix" permanently fixes the seeded bug for every call after it.

Bugs found while building this, before any live run

1. Package name collision. The vendored code_fix_agent/src/tools/ package (repo_explorer.py, git_ops.py, etc.) has the same name as the wrapper package this project's own tools live in. With both on sys.path, Python resolved import tools to whichever one came first and code-fix-agent's own internal imports (from tools.repo_explorer import write_file) broke with ModuleNotFoundError. Fixed by renaming this project's wrapper package to mcp_tools/ rather than touching the vendored code.
2. Vendored files assumed a src/ nesting level that wasn't there. retrieval.py, generation.py, and indexing.py compute PROJECT_ROOT = Path(__file__).resolve().parent.parent, correct in the original repo where they live at src/<file>.py one level under the project root -- but I'd initially copied them straight into vendor/rag_finance/, which put PROJECT_ROOT one directory too high and broke every relative data path (data/processed/finance_docs.json not found). Fixed by nesting them under vendor/rag_finance/src/ to match the layout the code actually assumes, instead of editing the vendored files.

Tests

pytest tests/ -v

6 tests: the server registers exactly the 3 expected tools with correct input schemas, ticker validation/normalization, and fix_code_bug's API-key guard -- all protocol-level, none need an Anthropic API key.

query_finance_filings's retrieval stage (BM25 + semantic + reranking) is verified working end-to-end against the real indexed filings -- confirmed it correctly isolates a single company's chunks from the shared 10-company corpus. Its generation stage, and all of fix_code_bug, need a funded Anthropic key to run past the point these tests reach -- not yet tested live, same status as the sibling projects.

Stack

Official mcp Python SDK (stdio transport) + the vendored RAG and LangGraph agent pipelines from rag-finance-assistant and code-fix-agent.

Status

Structurally verified: all 6 tests pass, tool registration/dispatch confirmed through the real MCP server object (not mocked), retrieval confirmed working against the real vector store. Generation (query_finance_filings's answer step) and the full fix_code_bug loop are code-complete but blocked on the same zero-credit Anthropic API key as the rest of this portfolio -- see Status in the sibling repos' READMEs.