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DocGraph

Documentation knowledge graph MCP server for LLM agents

MCP-native for LLM agents · CJK + Latin FTS5 · Multi-format graph

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Govern your documents like code. DocGraph indexes .md, .docx, .html, and .pdf into a graph and runs drift audits on them — stale policies, conflicting research claims, superseded ADRs, undocumented code exports — so you can review your doc corpus the way you review a codebase. Most doc tools index and search. DocGraph also tells you what's broken.

Drift audit on documents

docgraph_context format=drift_audit

Surfaces 14 finding codes across the corpus. A few:

• policy.stale_review — SOPs past their review_due date
• policy.superseded_referenced — docs citing a replaced policy
• policy.conflicting — same scope, contradicting rules
• research.competing_interpretations — claims that contradict
• research.unverified_evidence — assertions with no source
• research.superseded_claim — research overruled by a newer claim
• doc.stale_by_git — docs with no git commits in a long while
• code.undocumented_export — code surfaces with no doc anchor
• code.unanchored_feature — approved features with no code anchor

Three packs ship enabled (governance, research_provenance, entity); three are opt-in (policy_process, assessment_drift, code_doc). No code knowledge required for governance and research — they work on any document collection.

Opt-in agent enrichment, with provenance

Your .docx / .pdf / .html archive has no frontmatter, so it can't be governed. DocGraph fixes that without compromising authority:

agent → docgraph_enrichment(action=pending)
        ↳ scope (N docs), per-model USD estimate, sensitive paths flagged, token
user  → "go"
agent → runs LLM with its own key, then action=process for each doc
        ↳ stored as source=agent_inferred (advisory, lowest authority)
        ↳ logged with model_id, agent_id, run_id, content_hash

The confirmation token is batch-bound — one user consent authorizes the docs the user saw, no more. Sensitive paths silently refuse to issue tokens. agent_inferred metadata never overrides human frontmatter or extracted document metadata. Your governance survives the agent. DocGraph itself never calls an LLM. Enable with --enable-enrichment.

Other differentiators

• CJK + Latin search that actually works — FTS5 trigram, not English-only
• CodeGraph-style graph traversal for docs — docgraph_graph operation=incoming|outgoing|impact|trace
• Workspace fan-out — one MCP server, N projects, one query
• Reviewable evidence packs — format=context_pack returns indexed text, hashes, citations, impact (not a RAG black box)

What it isn't

A RAG black box, an embedding shop, or a Notion replacement. It's the layer that makes your existing docs auditable, navigable, and safe to feed to LLMs.

The LLM-facing fit guide — when DocGraph helps a project and when to use your own tools instead — is in AGENTS.md. Single binary, zero runtime dependencies, indexes hundreds of docs in seconds.

At a Glance

Metric	Value
Language	Go 1.25+
Binary size	~18 MB
Codebase	~21,770 lines of Go (+ ~26,430 lines of tests)
Index speed	70–700 files per project in 2–6s (full rebuild; --force)
Typical graph	~950 nodes and ~670 edges per 100 indexed files

Install

go install github.com/Detective-XH/docgraph@latest

Or build from source with version embedded:

git clone https://github.com/Detective-XH/DocGraph.git
cd DocGraph
go build -ldflags "-X main.version=$(git describe --tags --always)" -o docgraph .

Requires Go 1.25 or later.

go install does not support -ldflags injection, so docgraph version will output dev for binaries installed that way. Use the source build above to get a versioned binary.

CLI

docgraph init [--dry-run] [--interactive] [--install-clients auto|all|LIST] [--workspace] [--scope user] [--with-skills] [--update-skills] [path] # Create local config; optionally install MCP clients and bundled skills
docgraph install [--dry-run] [--interactive] [--clients auto|all|LIST] [--workspace] [--scope user] [--update-skills] [path]      # Configure MCP clients without re-initializing
docgraph pack list [--workspace] <path>                         # List domain packs and enabled state
docgraph pack enable [--workspace] [--no-sync] <pack-id> <path>  # Enable a domain pack; code_doc syncs by default
docgraph pack disable [--workspace] <pack-id> <path>             # Disable a domain pack; code_doc rows are removed
docgraph index [--force] [--threshold N] [--no-gitignore] [--no-history] <path>  # Index a project
docgraph sync [--threshold N] [--no-gitignore] [--no-history] <path>             # Incremental hash-based update
docgraph status <path>                       # Print index stats
docgraph serve [--threshold N] [--no-gitignore] [--no-history] [--max-watches N] [--enable-embeddings] [--enable-enrichment] --path <path>     # MCP stdio server (single project)
docgraph serve [--threshold N] [--no-gitignore] [--no-history] [--max-watches N] [--enable-embeddings] [--enable-enrichment] --workspace <dir> # MCP stdio server (auto-discover all child dirs)
docgraph version                             # Print build version

LIST is a comma-separated client list: claude,codex,hermes,opencode. auto always writes project-local Claude Code config and also writes Codex, Hermes, and OpenCode config when their config directories already exist. all creates config files for every supported client. Use --dry-run to print create/update/unchanged actions without writing files. Use --interactive to print the same review and confirm before writes.

Bundled Skills

When installing for Claude Code, DocGraph automatically installs companion skills into .claude/skills/ alongside the MCP config — no extra flag needed:

docgraph init --install-clients claude /path/to/project  # MCP config + skill
docgraph install --clients claude /path/to/project       # MCP config + skill

To install skills on a project that was already initialized without --install-clients:

docgraph init --with-skills /path/to/project

Skills are installed with skip-if-exists policy — safe to re-run. To update an existing skill to the latest bundled version:

docgraph init --update-skills /path/to/project
docgraph install --clients claude --update-skills /path/to/project

The docgraph-drift-audit skill audits all indexed .md files for DocGraph compatibility: missing frontmatter, isolated docs (no outgoing links), broken wikilinks, headings, and similarity islands. Reports PASS/FAIL per category and offers auto-fix via docgraph_files and docgraph_similar.

Available skills bundled in the binary:

Skill	Purpose
docgraph-drift-audit	Audit .md files for DocGraph compatibility
policy-drift-audit	Display and triage policy/process drift findings from docgraph_context format=drift_audit
assessment-drift-audit	Display and triage research assessment drift findings from docgraph_context format=drift_audit
code-doc-drift-audit	Display and triage docs-code drift findings (code.*) when the code_doc pack is enabled

MCP Tools

docgraph_graph supports operation=incoming|outgoing|impact|trace. Use document for incoming, outgoing, and impact; use from and to for trace.

Tools

#	Tool	Description
1	docgraph_search	FTS5 full-text search (CJK + Latin) with section-level results, field-weighted ranking, graph-aware and git-history-aware reranking, and governance/research/entity filters. Returns documentation only by default; pass include_code=true or kind=code_file to include code_doc-pack code files
2	docgraph_context	Primary entry point -- task context with related docs, structure, cross-refs, and bounded source content. Use format=context_pack for reviewable evidence packs; format=drift_audit for policy/process, research, and (when code_doc is enabled) docs-code drift audit reports
3	docgraph_graph	Graph traversal facade. operation=incoming (who references this doc), operation=outgoing (what this doc links to), operation=impact (blast radius, configurable depth), operation=trace (shortest path between two docs). Use document= for incoming/outgoing/impact; from= and to= for trace
4	docgraph_node	Single document details with metadata, structure, and edges
5	docgraph_explore	Survey multiple related documents in one call
6	docgraph_files	Indexed file tree
7	docgraph_similar	Find topically similar documents (TF-IDF + shared refs + tags; engine=auto/tfidf/neural)
8	docgraph_status	Index health (files/nodes/edges/unresolved/DB size), per-project stats, neural embedding model totals, domain packs, metadata quality, enrichment coverage, LLM callout tool state (embeddings/enrichment enabled/disabled + required flags), and compact drift audit summary when policy/research findings exist
9	docgraph_tags	List all tags with doc counts, or filter documents by tag
10	docgraph_history	Git commit history for a document: amendment count, authors, dates. Collected by default during indexing; --no-history opts out.
11	docgraph_enrichment	Opt-in (--enable-enrichment). Pull or store inferred summaries and metadata for documents without frontmatter. Facade: action=pending|process
12	docgraph_embeddings	Opt-in (--enable-embeddings). Neural embedding workflow facade. action=pending lists docs needing embeddings; action=store saves a vector and recomputes neural similarity; action=clear deletes all embeddings for a model

Start with docgraph_context for any research question. It composes search, structure, and cross-references into a single result. Use the other tools to drill into specifics.

For the agent-facing decision of whether to install/use DocGraph at all, see AGENTS.md. Once installed, tool-selection rules are in the MCP serverInstructions (injected each session) and the per-tool descriptions.

Agent Metadata Enrichment

The full mechanics of the opt-in workflow summarized at the top of this README. DocGraph never calls an LLM itself — your agent does, with its own key, then writes results back with provenance.

1. docgraph_enrichment(action=pending, limit, content_mode) returns frontmatter-less documents without a current inferred summary, including doc_id, content_hash, and bounded content. The response includes a CONFIRMATION_TOKEN bound to the batch of doc_ids it lists.
2. The agent infers a concise summary and optional metadata JSON object.
3. docgraph_enrichment(action=process, doc_id, content_hash, summary, metadata, confidence, model_id, provider, agent_id, confirmation_token) stores the result. model_id is required, content_hash must match the pending response, and confirmation_token must be the one returned by action=pending for a doc_id in that batch.

Inferred metadata never overrides authored frontmatter or extracted document metadata. Stored summaries appear in docgraph_node, docgraph_context, and context packs. docgraph_status reports enrichment coverage and stale results. Normal retrieval uses one current enrichment per document, while DocGraph keeps an internal run ledger with model, provider, agent, and content-hash provenance. Agent-inferred summaries and metadata are advisory context, not source of truth.

Privacy: docgraph_enrichment action=pending returns document content that your agent may send to an external provider. Get user consent before proceeding.

Semantic Similarity

DocGraph computes topic similarity between documents using three signals:

Signal	Method	Weight
Text overlap	TF-IDF cosine similarity	50%
Shared references	Jaccard similarity of outgoing link targets	30%
Tag overlap	Jaccard similarity of frontmatter tags	20%

Documents scoring above the threshold (default 0.25) are connected with similar_to edges. This finds conceptually related documents even when they don't explicitly link to each other — the key advantage over grep-based search.

Similarity is computed automatically during indexing. Query with docgraph_similar. Tune sensitivity with --threshold N on index, sync, or serve; lower values create more similar_to edges.

Neural Embeddings (agent-driven)

DocGraph never calls an LLM itself. Instead, your agent computes embeddings with any provider and pushes the vectors back — a pull-then-push agentic workflow that enables semantic search far beyond TF-IDF vocabulary matching.

1. docgraph_embeddings(action=pending, model_id, limit, content_mode) — returns docs without up-to-date embeddings, including content and content_hash. content_mode=full (default) reads the full section from disk; content_mode=excerpt uses the stored body excerpt. Different model_id values are partitioned separately and never compared with each other.
2. Your agent computes vectors with its own provider (OpenAI, Ollama, Nomic, etc.)
3. docgraph_embeddings(action=store, doc_id, model_id, vector, content_hash) per doc — stores the vector and recomputes neural similar_to edges. Pass content_hash exactly as returned by step 1.
4. docgraph_similar deduplicates TF-IDF and neural results for the same pair, preferring neural when both exist.

In workspace mode, both embedding workflows automatically locate the correct per-project store by doc_id.

Privacy: pending embedding actions return document content that your agent will send to an external provider. Get user consent before proceeding.

Use docgraph_embeddings(action=clear, model_id) to delete all vectors for a model and reclaim space. docgraph_status shows a Neural Embeddings table listing stored models, total vectors, and stale count.

Node and Edge Kinds

Nodes: document, heading, definition, tag; optional code_file nodes when the code_doc domain pack is enabled.

Edges:

Kind	Meaning
contains	Document contains heading/definition
references	[text](path.md) Markdown link
wikilinks_to	[[target]] wikilink
related_to	Frontmatter wikilink (e.g., related_to: "[[target]]")
similar_to	Topic similarity (TF-IDF + shared refs + tags; or neural if embeddings stored)
tagged	Frontmatter tag association
embeds	![[embed]] transclusion
links_external	URL to external resource

What Gets Indexed

Markdown (.md) — up to 1 MB per file:

• YAML frontmatter parsed into metadata; headings and **Term:** definition lines produce structural nodes
• [[wikilinks]], [links](path.md), ![[embeds]], external URLs, and frontmatter tags produce typed edges

Word documents (.docx) — up to 10 MB per file:

• Heading paragraphs (Heading 1–6 styles) become heading nodes with containment edges
• Hyperlinks extracted as docx_hyperlink edges; Dublin Core metadata (core.xml) stored as key/value tuples
• Zip-slip protection, per-entry size limits, 50 MB total uncompressed budget

HTML (.html, .htm) — up to 5 MB per file:

• <h1>–<h6> tags (including id attributes) become heading nodes
• <meta name=…> and <meta property=…> stored as metadata tuples; <a href=…> become typed link edges
• <script> and <style> content excluded from body text and section chunks

PDF (.pdf) — up to 50 MB / 500 pages per file:

• Each page becomes a heading node and a section chunk
• Info-dict fields (Title, Author, Subject, Keywords, CreationDate) indexed as metadata tuples
• Image-only PDFs detected via average chars/page and flagged with warning: image-only-pdf
• Predefined CMap fonts decoded natively: Uni*-UCS2-* (UniGB/CNS/JIS/KS), 90ms-RKSJ-* (Shift-JIS), GBK-EUC-H/V (Simplified Chinese), ETen-B5-H/V (Traditional Chinese), KSCms-UHC-H/V (Korean). Pages that still cannot be decoded are flagged with warning: extraction-failed:encoding-garbage and skipped rather than indexed with replacement-character garbage

Code documentation surfaces (opt-in) — up to 1 MB per file:

• Enable the code_doc domain pack to index file headers, exported doc comments, test names, and example names:
  • Single project: docgraph pack enable code_doc /path/to/project
  • Workspace: docgraph pack enable --workspace code_doc /path/to/workspace
  • Inspect state: docgraph pack list /path/to/project
• Supported languages include Go, Python, Ruby, JavaScript, TypeScript, Svelte, Vue, Rust, C, C++, Java, Swift, C#, PHP, Kotlin, Dart, Lua, Luau, Pascal, SQL, and Liquid
• Adds one code_file node per source file; incremental pack enable sync completes in 1–4s for 40–80 code files, up to ~12s for 300+ code files
• After enabling, docgraph_search still returns documentation only by default — opt code files in with kind=code_file or include_code=true — and format=drift_audit surfaces code.* findings
• --force re-index resets domain pack state — re-run docgraph pack enable code_doc <path> after a force rebuild
• This is shallow documentation indexing only; CodeGraph remains the intended tool for call graphs, type resolution, routes, and code impact

Common rules:

• Respects .gitignore and .docgraphignore
• Skipped directories: node_modules, .git, target, dist, build, vendor, .next, .cache, __pycache__, .codegraph, .docgraph, .obsidian, and .claude/worktrees (agent git worktrees — full repo copies that would index as duplicates). These are pruned unconditionally — --no-gitignore lifts .gitignore rules but does not re-include them. (For Obsidian vaults this means the .obsidian/ app-config dir is skipped while your notes are still fully indexed.)

Domain Packs

Domain packs extend the metadata schema for specific use cases. Three packs are enabled by default; three are opt-in.

Pack	Default	Domain	Purpose
governance	On	governance	Lifecycle status, ownership, sensitivity, review scheduling, audience access controls, and document supersession
research_provenance	On	research	Claims, evidence, source type, confidence, analyst workflow, event/assessment dates, and temporal validity
entity	On	entity	Entity classification, canonical naming, and alias declaration; activates the entity source graph
code_doc	Off	code	File headers, doc comments, test names, and example names from Go, Python, JS/TS, Rust, and 20+ more languages
policy_process	Off	policy_process	Policy/SOP drift detection — conflicting, stale, duplicated, superseded, and non-canonical documents
assessment_drift	Off	research	Assessment drift detection — stale assessments, unverified evidence, and competing research interpretations

Frontmatter Fields by Pack

Each pack reads specific keys from your Markdown frontmatter.

governance — lifecycle and access control:

status: active            # Governance lifecycle status
owner: alice              # Accountable person or role
sensitivity: internal     # Sets retrieval boundaries
allowed_audience: [engineering, legal]
review_due: 2026-12-31    # Triggers policy.stale_review when overdue
effective_date: 2026-01-01
canonical_source: true    # Marks as the authoritative copy among duplicates
approver: bob
department: Engineering
supersedes: old-policy.md
superseded_by: new-policy.md

research_provenance — evidence and provenance tracking:

claim_id: CLM-001
source_type: primary      # primary | secondary | internal
confidence: high
analyst_status: verified
assessment_date: 2026-05-01
event_date: 2026-04-15
last_verified: 2026-05-20
valid_until: 2026-11-01   # Triggers research.stale_assessment when expired
evidence: [doc/evidence-a.md, doc/evidence-b.md]
client: ACME
deliverable_id: RPT-42

entity — canonical entity declaration:

entity_type: organization   # person | organization | location | …
canonical_name: Acme Corp
aliases: [ACME, Acme Corporation]

policy_process (opt-in) — SOP and policy enrichment:

sop_category: onboarding
policy_domain: HR           # HR | Security | Finance | …
process_owner: People Ops
version: "2.1"
conflict_resolution: supersedes-v2.0

assessment_drift (opt-in) — competing research tracking:

contradicts: assessment-2026-03.md
supersedes_claim: CLM-099

Drift Audit Findings

docgraph_context format=drift_audit surfaces advisory findings from enabled packs. No code knowledge is needed — governance and research packs work on any document collection (.md, .docx, .html, .pdf).

Finding	Pack(s) required	What it detects
policy.stale_review	governance	review_due has passed
policy.superseded_referenced	governance	Superseded doc is still cited by others
policy.duplicate	governance	Near-duplicate content detected via similarity
policy.non_canonical	governance	No canonical_source marker among near-duplicates
policy.conflicting	governance	Similar docs with conflicting status or effective dates
research.stale_assessment	research_provenance	valid_until has expired
research.unverified_evidence	research_provenance	Evidence reference cannot be resolved
research.competing_interpretations	research_provenance + assessment_drift	Conflicting claims on the same topic
research.superseded_claim	research_provenance + assessment_drift	Outdated claim still cited
research.impacted_deliverable	research_provenance	Deliverable depends on a stale claim
doc.stale_by_git	none (git history)	No git commits in over N days (default 365), independent of frontmatter dates
code.missing_symbol	code_doc	Doc references a code symbol that no longer exists
code.undocumented_export	code_doc	Exported symbol has no doc comment
code.unanchored_feature	code_doc + governance	Feature mentioned in docs has no matching code

Managing Packs

docgraph pack list /path/to/project                                # Show all packs and enabled state
docgraph pack enable policy_process /path/to/project               # Enable an opt-in pack
docgraph pack enable assessment_drift /path/to/project
docgraph pack enable code_doc /path/to/project                     # Also triggers incremental sync
docgraph pack disable code_doc /path/to/project                    # Removes code_file rows
docgraph pack enable --workspace policy_process /path/to/workspace # Apply to all child projects

--force re-index resets all pack state — re-run docgraph pack enable <pack-id> <path> after a force rebuild.

Workspace Mode

Point DocGraph at a parent directory and it auto-discovers all immediate child directories as separate projects:

docgraph serve --workspace /path/to/workspace

• Each project gets its own .docgraph/docgraph.db (add .docgraph/ to .gitignore)
• Cross-project search fans out to all databases
• File watcher (fsnotify, 2s debounce) monitors served projects for live re-indexing
• Watch set is capped per process (--max-watches, default 8192; 0 = unlimited). Every watched directory/file is one descriptor on macOS, so an unbounded recursive watch of a very large tree can drive the OS file-descriptor table toward exhaustion (worse: one such process per connected client). The cap holds open descriptors to roughly the cap — plus the widest single watched directory, which fsnotify opens eagerly — instead of one per file in the whole tree. Beyond the cap, changes do not auto-reindex; run docgraph sync or restart. Override with the flag or DOCGRAPH_MAX_WATCHES.
• No configuration file needed

File Exclusion

DocGraph respects .gitignore by default. For additional control, create a .docgraphignore file (same syntax as .gitignore):

# Project-level .docgraphignore — exclude files within a project
drafts/
archive/
*.draft.md
!archive/INDEX.md    # re-include a specific file

Workspace-level .docgraphignore (at the workspace root) excludes entire projects by directory name:

# Workspace-level .docgraphignore — exclude projects
OSINT-Platform-backup-20260518
csint-private

Indexing all files

To index files that are gitignored (e.g., .claude/skills/, memory/ directories), use the --no-gitignore flag:

docgraph index --no-gitignore <path>
docgraph sync --no-gitignore <path>
docgraph serve --no-gitignore --workspace <dir>

This ignores .gitignore rules but still respects .docgraphignore.

MCP Client Integration

DocGraph works with any MCP-compatible client via stdio transport.

For automatic setup:

docgraph init --install-clients auto /path/to/project
docgraph install --clients all --workspace /path/to/workspace

The installer writes:

Client	Config target
Claude Code	/path/to/project/.mcp.json
Codex	$CODEX_HOME/config.toml or ~/.codex/config.toml
Hermes Agent	~/.hermes/config.yaml
OpenCode	project opencode.json / .opencode.json, otherwise $XDG_CONFIG_HOME/opencode/opencode.json

Claude Code

Project-level (this project only) — add to .mcp.json in your project root, or run:

docgraph init --install-clients claude /path/to/project

Manual .mcp.json:

{
  "mcpServers": {
    "docgraph": {
      "command": "docgraph",
      "args": ["serve", "--path", "."]
    }
  }
}

User-level (global) — available across all projects. Writes to ~/.claude.json via the claude CLI:

docgraph install --clients claude --scope user --workspace /path/to/workspace

Or manually with the claude CLI:

claude mcp add --scope user docgraph -- docgraph serve --workspace /path/to/workspace

Verify the connection:

claude mcp list

Important: Claude Code stores user-scope MCP config in ~/.claude.json, not ~/.claude/mcp.json. Manually editing ~/.claude/mcp.json has no effect — use claude mcp add --scope user or the project-level .mcp.json approach instead.

PATH note: docgraph must be on your PATH. For go install builds, ensure $GOPATH/bin is in your PATH (run go env GOPATH to find the location). If not, use the absolute path to the binary.

Codex (OpenAI)

Add to your MCP configuration:

[mcp_servers.docgraph]
command = "docgraph"
args = ["serve", "--workspace", "/path/to/workspace"]

Hermes Agent

Add to ~/.hermes/config.yaml:

mcp_servers:
  docgraph:
    command: docgraph
    args:
      - serve
      - --workspace
      - /path/to/workspace

OpenCode

Add to your opencode MCP configuration:

{
  "mcpServers": {
    "docgraph": {
      "command": "docgraph",
      "args": ["serve", "--workspace", "/path/to/workspace"]
    }
  }
}

Any MCP client

DocGraph uses stdio transport. Launch with:

docgraph serve --workspace /path/to/workspace
# or single project:
docgraph serve --path /path/to/project

The server reads JSON-RPC from stdin and writes to stdout.

Architecture

scan .md / .docx / .html / .pdf  (docformat registry: extensions + per-format size limits)
  -> dispatch:
       .md          → goldmark + inlined YAML frontmatter parser
       .docx        → stdlib archive/zip + encoding/xml
       .html / .htm → golang.org/x/net HTML tokenizer
       .pdf         → Detective-XH/gopdf (ledongthuc/pdf fork; text layer + CJK CMaps; writes to temp file)
       code docs    → optional code_doc pack for comments/tests/examples
  -> extract nodes, edges, links, metadata tuples, and section chunks
  -> store in SQLite (modernc.org/sqlite, pure Go)
  -> resolve cross-document references
  -> compute topic similarity (TF-IDF + graph Jaccard)
  -> serve over MCP stdio (mark3labs/mcp-go)

FTS5 uses the trigram tokenizer for mixed CJK and Latin full-text search.

Dependencies

Dependency	Role
modernc.org/sqlite	Pure-Go SQLite driver (no CGo) with FTS5
goldmark	Markdown parser
yaml.v3	YAML frontmatter parsing
mcp-go	MCP protocol (stdio transport)
fsnotify	Cross-platform file watcher
golang.org/x/net	HTML tokenizer for .html/.htm extraction
Detective-XH/gopdf	PDF text-layer extraction (fork of ledongthuc/pdf adding CJK CMap decoders)
stdlib	.gitignore + .docgraphignore matching, archive/zip + encoding/xml for .docx

Supply Chain

CI verifies module checksums with go mod verify, runs govulncheck, and generates a CycloneDX JSON SBOM artifact named docgraph-sbom with cyclonedx-gomod. The SBOM is generated from go.mod during GitHub Actions runs; generated SBOM files are not checked into the repository.

CodeGraph Interoperability

DocGraph and CodeGraph are complementary. DocGraph owns documentation context, governance/research metadata, citation paths, document references, context packs, drift audits, and shallow code-documentation surfaces. CodeGraph owns source-code intelligence such as symbols, callers/callees, call traces, route handlers, and code impact.

CodeGraph interoperability currently ships as an advisory handoff layer in the MCP server instructions. DocGraph does not call CodeGraph, read .codegraph/, or import CodeGraph symbol anchors. The reserved codegraph_anchor metadata field stays empty until CodeGraph exposes a stable export/API contract.

For docs-code work, enable DocGraph's code_doc pack — it is the interface layer between DocGraph and CodeGraph. DocGraph indexes documentation surfaces (file headers, exported doc comments, test names, example names); CodeGraph indexes code structure (symbols, callers/callees, call graphs, type resolution). Together they give a complete picture: format=drift_audit with code_doc enabled can surface code.missing_symbol, code.undocumented_export, and code.unanchored_feature findings, then hand symbol-level questions to codegraph_* tools when the agent environment exposes them.

Inspired By

DocGraph is inspired by CodeGraph, which builds a knowledge graph from source code symbols using tree-sitter and SQLite. DocGraph adopts the same core design:

• Schema: nodes + edges + files + unresolved_refs + FTS5 + section_chunks + section_chunks_fts + document_metadata + governance_metadata + research_metadata + domain_packs + domain_pack_fields + entities + entity_mentions — the graph model extended with section snapshots, section-level search, normalized governance metadata, research provenance, domain schema pack registration, and entity/source graph primitives. Schema is bootstrapped via idempotent CREATE TABLE/INDEX/TRIGGER IF NOT EXISTS on every open; if the shape needs to change, delete .docgraph/ and reindex.
• Pipeline: scan → parse → store → resolve — the same four-phase indexing pipeline, with goldmark replacing tree-sitter for AST extraction.
• Two-phase resolution: raw links are extracted during parsing, then resolved in a separate pass after all files are indexed — identical to CodeGraph's UnresolvedReference → ReferenceResolver pattern.
• MCP tool surface: 10 default tools with CodeGraph-compatible naming for context, search, node, explore, similar, files, status, tags, history, plus graph traversal (docgraph_graph); 2 additional LLM-callout tools (docgraph_embeddings, docgraph_enrichment) register only when their --enable-* flags are set. Graph traversal, embeddings, and enrichment are facade tools that group fine-grained operations behind a single dispatch parameter, keeping agent-facing instructions compact.

Where they diverge: DocGraph is written in Go (single binary, no Node.js runtime), uses the trigram tokenizer for CJK support, and adds workspace mode for multi-project fan-out queries — features that reflect documentation use cases rather than code navigation. DocGraph also adds hybrid topic similarity (TF-IDF + graph Jaccard + tags) to discover conceptual relationships that neither explicit links nor code structure can capture.

Release v0.3.0 — SHA-256 Checksums

Signed by EDB0808F3F248B66F53837B4888293C4BA30EEF6 (Xavier).

docgraph-darwin-arm64.tar.gz

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docgraph-darwin-amd64.tar.gz

4a63650adcff4364883a5d96b502b022171e61456b4486823570b0bd69be46a9

docgraph-linux-amd64.tar.gz

cd9d3092a367ca1180e7e1886fb9a61e6efd98abc872e9381a358d15c4f77681

docgraph-linux-arm64.tar.gz

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docgraph-windows-amd64.zip

4f5063b5cef521797cf4476db0a85edd00522493a991b4f74c83f0fc5609a96e

Verify:

gpg --verify SHA256SUMS.asc SHA256SUMS
shasum -a 256 -c SHA256SUMS

License

MIT