MCP server that makes any Hugo site's content queryable via SQLite with FTS5 full-text search
Project description
hugo-memex
MCP server that makes any Hugo site's content queryable via SQLite with FTS5 full-text search.
Your Hugo blog is ground truth. hugo-memex indexes it into a SQLite cache with full-text search, taxonomy queries, and JSON front matter extraction : then exposes it via MCP so AI assistants can query, search, and create content.
Install
pip install hugo-memex
Quick Start
# Configure
mkdir -p ~/.config/hugo-memex
cat > ~/.config/hugo-memex/config.yaml << 'EOF'
hugo_root: ~/path/to/your/hugo-site
database_path: ~/.config/hugo-memex/hugo.db
EOF
# Index your site
hugo-memex index
# Query it
hugo-memex search "machine learning"
hugo-memex sql "SELECT title, section, date FROM pages ORDER BY date DESC LIMIT 10"
hugo-memex stats
MCP Integration
Add to your .mcp.json for Claude Code:
{
"mcpServers": {
"hugo-memex": {
"command": "python",
"args": ["-m", "hugo_memex", "mcp"],
"env": {
"HUGO_MEMEX_CONFIG": "/path/to/config.yaml"
}
}
}
}
Tools
| Tool | Purpose |
|---|---|
execute_sql |
Read-only SQL with ~10 exemplar queries in the docstring |
get_pages |
Bulk content retrieval : filter by section, tag, FTS search, paths |
get_content |
Raw markdown from filesystem for a single file |
create_page |
Create new content with proper leaf bundle structure |
update_page |
Merge front matter / replace body on existing pages |
suggest_tags |
FTS5-based tag suggestions with canonical casing |
get_front_matter_template |
Derive section conventions from actual data |
validate_page |
Check completeness, tag consistency, cross-references |
rebuild_index |
Incremental re-sync after content changes |
Resources
| Resource | Purpose |
|---|---|
hugo://schema |
Full DDL + relationship docs + query patterns |
hugo://site |
Hugo site config (hugo.toml) as JSON |
hugo://stats |
Aggregate stats for quick orientation |
Architecture
- DB is a read-only cache : Hugo content files are ground truth
- Generic schema : JSON
front_mattercolumn, no per-content-type tables - Taxonomies auto-discovered from
hugo.toml - Incremental sync via SHA-256 content hash + file mtime
- FTS5 with porter stemming + unicode61 tokenizer
- SQLite authorizer enforces read-only (not bypassable via PRAGMA)
- Raw
sqlite3: no ORM. WAL mode, foreign keys.
Configuration
# ~/.config/hugo-memex/config.yaml
hugo_root: ~/github/repos/my-hugo-site # contains hugo.toml + content/
database_path: ~/.config/hugo-memex/hugo.db
Environment variable overrides: HUGO_MEMEX_CONFIG, HUGO_MEMEX_HUGO_ROOT, HUGO_MEMEX_DATABASE_PATH.
License
MIT
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file hugo_memex-0.1.0.tar.gz.
File metadata
- Download URL: hugo_memex-0.1.0.tar.gz
- Upload date:
- Size: 33.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8dcf79f6564a9328b9df65bbb5844e582dc257c677ade68e21c3a83a74532022
|
|
| MD5 |
59f11aefb0dee43b387bcb4c8bb45b4c
|
|
| BLAKE2b-256 |
e0f081a4c95ec73a895db97face947efbf9baad83493e05e262664a57e6211fa
|
File details
Details for the file hugo_memex-0.1.0-py3-none-any.whl.
File metadata
- Download URL: hugo_memex-0.1.0-py3-none-any.whl
- Upload date:
- Size: 24.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
07bcb5b7dd1f25ca461c6d2281c844b58345485fef9bf97ffd1410fc3e658306
|
|
| MD5 |
9a210c5c72d0479c507e40b61771c733
|
|
| BLAKE2b-256 |
a2680a28a3864a0dc463c43bcada85750ac148b515e17ef7e7f4fa1bbcfd9d98
|