banhmi：面向东南亚银行金融法规的可引用 MCP 语料库与服务器

A citable regulatory corpus and Model Context Protocol (MCP) server for Southeast Asian banking, finance, and technology law.

Documentation · Architecture · Roadmap

banhmi collects legal documents from government, regulator, and supplementary legal-data sources. It extracts their text and serves ranked evidence over MCP. Results include native citations, validity, amendment relations, provenance, source links, and known coverage gaps.

banhmi does not answer legal questions. A connected agent retrieves the evidence and forms the answer.

Connect to a live corpus

The public endpoints use MCP over Streamable HTTP. They require no signup or API key.

Those statements describe the current AWS deployment verified on 2026-08-14. The repository now contains a later authenticated Vietnam server composition, but that source has not been deployed or verified with Google or an MCP client. See the authenticated access runbook for its pending release gates.

Add one endpoint to an MCP client that supports Streamable HTTP. Search in the language shown above. The connected agent can translate the question before searching and translate the retrieved evidence afterward.

The server exposes five tools:

For example, ask: What are the technology risk management requirements for banks?

What it provides

• Scope-filtered discovery for banking and financial regulation plus related technology law, including cybersecurity, data protection, artificial intelligence, cloud, electronic transactions, payments, and digital banking.
• Text extracted from each cited source without paraphrasing. Each result links back to its source so the wording can be checked.
• Native provision structure, such as Vietnamese Điều/Khoản, Indonesian Pasal/ayat, and Section/Subsection for Malaysia and Singapore.
• Effective dates, current-law filtering, recorded amendment and repeal relations, provenance, and explicit data gaps.
• Hybrid retrieval over dense Qwen3 embeddings and BM25 sparse vectors, fused with reciprocal rank fusion (RRF).

Each country has its own corpus and database. Sources and language rules are selected by configuration, not by maintaining country-specific forks. See the source design and jurisdiction registry.

Architecture

flowchart TB
  subgraph WRITE["Write path: cmd/pipeline"]
    DISC["Discover"] --> FETCH["Fetch official files"]
    FETCH --> EXT["Extract"]
    EXT --> NORM["Normalize structure, validity, relations"]
    NORM --> IDX["Chunk and index"]
  end

  GPU["Kaggle T4 GPU<br/>Qwen3 bulk embedding"]
  IDX <-->|"dataset I/O"| GPU

  DB[("AWS RDS PostgreSQL 17 + pgvector<br/>one database per country")]
  IDX -->|"write over TLS"| DB

  subgraph READ["Read path: AWS ECS on EC2"]
    MCP["One slim MCP service<br/>routes all six jurisdictions"]
    EMB["Shared cmd/embedder service<br/>Qwen3 ONNX FP16"]
    MCP -->|"query text"| EMB
  end

  DB -->|"corpus read"| MCP
  CF["CloudFront<br/>six HTTPS domains"] --> MCP
  USERS["User-owned agents"] -->|"MCP over Streamable HTTP"| CF

Loading

The ingestion pipeline uses three data layers:

1. Bronze: discover and fetch source records and files.
2. Silver: extract text and normalize structure, validity, and relations.
3. Gold: create provision-aware chunks, dense embeddings, and BM25 sparse vectors.

Production runs one slim MCP service for all six jurisdictions and one shared query-embedding service. PostgreSQL remains the jurisdiction boundary: each country has a separate database. See Architecture and Deployment.

Corpus and retrieval status

These corpus sizes were verified in production on 2026-08-14. The evaluation metrics are accepted offline baselines recorded from 2026-07-25 through 2026-07-27. Call corpus_status for current live counts.

Recall@8 measures whether expected citations appear in the first eight results. Current-law precision measures whether returned primary hits are in force. Abstention measures whether the retriever flags questions that lack usable in-scope evidence. See the evaluation design and roadmap for details and known gaps.

Contribute and self-host

Read Development and verification for the hosted contribution workflow, initial GitHub checks, and checks that still need hosted infrastructure. The repository cleanup plan records the current documentation and CI work.

Self-hosting requires PostgreSQL 17 with pgvector, the Go services, and a matching Qwen3-Embedding-0.6B query embedder. Building a corpus can also require object storage, bulk embedding, OCR, and source-specific network access. Deployment defines the portable runtime contract and reference deployment.

Documentation

• Documentation index
• Architecture
• Development and verification
• Contributor instructions
• Current repository cleanup plan
• Deployment
• Publishing
• Roadmap and current status
• ASEAN Banking MCP redesign proposal
• Source, pipeline, schema, extraction, retrieval, and workflow evaluation designs
• Jurisdiction registry and country guides

License

Apache 2.0.