About Ogm MCP Skills
Ogm MCP Skills is an MCP server published by ardiannurcahya in the Developer Tools category: mCP Server and AI Agent Skills for OpenGraphMemory.
The repository has 5 stars and 2 forks, with the last commit a month ago. Recent commit activity is the strongest signal that reported issues will get attention.
Install
git clone https://github.com/ardiannurcahya/ogm-mcp-skillsThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Ask AI
Ask AI about Ogm MCP Skills
Powered by Claude · Grounded in docs
Security checks
Static checks derived from the repository 10 hours ago. Heuristics on the source, not an audit.
- ✓README presentThe repository ships documentation.
- ✓License declaredUsable under a stated license.
- ✓Tests presentA test suite exists in the repository.
- ✓Dependencies pinnedA lockfile pins dependency versions.
- ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
1 check has not been run yet.
Releases
README
ogm-mcp-skills
MCP Server & AI Agent Skills for OpenGraphMemory and Codebase Knowledge Graphs.
Overview · Tools (29) · Integration Modes · Installation · Quick Setup · Client Configs
MCP stdio server and AI Agent Skills for Google Antigravity, Cursor, Claude Code, OpenCode, Hermes Agent, OpenClaw, and OpenAI Codex to OpenGraphMemory and the Codebase Knowledge Graph.
The MCP server uses authenticated OpenGraphMemory REST APIs only. It is stateless: no local database, session mapping, direct PostgreSQL, Neo4j, or object-store access.
Status
Alpha. PyPI releases are published from GitHub Actions on v* tags. Source install is also supported for development.
Tools
ogm_healthogm_list_datasetsogm_search_entitiesogm_get_entityogm_get_neighborsogm_find_pathogm_get_subgraphogm_get_graphogm_get_evidenceogm_get_relation_evidenceogm_retrieval_queryogm_upload_documentogm_memory_list_episodesogm_memory_get_episodeogm_memory_searchogm_memory_create_episodeogm_memory_append_attemptogm_memory_record_outcomeogm_memory_feedback_episodeogm_memory_supersede_episodeogm_memory_feedback_patternogm_memory_supersede_patternogm_search_code_symbolsogm_get_code_call_graphogm_get_code_chunksogm_recall_code_memoryogm_record_code_fixogm_sync_code_fileogm_index_codebase
Read tools inspect PostgreSQL-authoritative graph and Agent Memory data. Agent Memory results are historical claims: inspect recorded evidence and verifiers before relying on them. personal-safe permits reviewed document upload, additive Agent Memory records, and code sync; memory-curator additionally permits memory feedback and supersession. No delete, admin, project-create, relation-review, analytics-refresh, semantic-retrieval, or automatic conversation-ingestion tools exist.
Install
Install from PyPI with uv:
uv tool install ogm-mcp-skills
Or run without installing:
uvx ogm-mcp-skills==0.2.3 --version
Automated 1-Command Setup
Automatically copy SKILL.md and merge MCP server configuration into your installed agent harness (Antigravity, Gemini CLI, Claude Desktop, Cursor, etc.):
ogm-mcp-skills setup
Or run directly without installing:
uvx ogm-mcp-skills setup
For source development:
git clone https://github.com/ardiannurcahya/ogm-mcp-skills.git "$HOME/src/ogm-mcp-skills"
cd "$HOME/src/ogm-mcp-skills"
uv sync --locked
Integration Modes: On-Demand Skill vs. Always-On Directives
Choose the integration pattern that best fits your workflow:
| Integration Mode | Primary File | How It Works | Best For |
|---|---|---|---|
| On-Demand Skill | SKILL.md |
Dynamically evaluated when user prompts match keyword triggers. | Modular setups where OGM is invoked only when explicitly needed. |
| Always-On Directive | AGENTS.md / CLAUDE.md / GEMINI.md / .cursor/rules/ogm.mdc |
Injected into the agent's system prompt on every session and turn. No triggers required. | Production codebases where agents must deterministically check memory, sync AST, and persist fixes. |
Enabling Always-On Mode
Copy the directive example matching your AI harness into your workspace root:
- Universal / OpenClaw / Codex:
cp examples/AGENTS.md.example AGENTS.md - Cursor:
cp examples/cursor/.cursor/rules/ogm.mdc.example .cursor/rules/ogm.mdc - Claude Code:
cp examples/claude-code/CLAUDE.md.example CLAUDE.md - Google Antigravity:
cp examples/antigravity/GEMINI.md.example GEMINI.md
Configure
Set these environment variables before starting your MCP client:
OGM_BASE_URL=http://localhost:8000
OGM_API_KEY=<project-api-key>
OGM_PROJECT_ID=<project-uuid>
OGM_PERMISSION_PROFILE=read-only
Use OGM_PERMISSION_PROFILE=read-only for graph and Agent Memory retrieval. Use OGM_PERMISSION_PROFILE=personal-safe for reviewed uploads and additive Agent Memory records. Use memory-curator only for reviewed feedback and supersession.
Optional upload roots:
OGM_UPLOAD_ROOTS=/absolute/path/to/allowed/docs
More options: Configuration.
MCP Client Setup
Claude Code
Add MCP server config to project .mcp.json:
{
"mcpServers": {
"ogm": {
"command": "uvx",
"args": ["ogm-mcp-skills==0.2.3"],
"env": {
"OGM_BASE_URL": "${OGM_BASE_URL}",
"OGM_API_KEY": "${OGM_API_KEY}",
"OGM_PROJECT_ID": "${OGM_PROJECT_ID}",
"OGM_PERMISSION_PROFILE": "${OGM_PERMISSION_PROFILE}"
}
}
}
}
Verify:
claude mcp list
OpenCode
Add MCP server config to opencode.json or opencode.jsonc:
{
"mcp": {
"ogm": {
"type": "local",
"command": ["uvx", "ogm-mcp-skills==0.2.3"],
"environment": {
"OGM_BASE_URL": "{env:OGM_BASE_URL}",
"OGM_API_KEY": "{env:OGM_API_KEY}",
"OGM_PROJECT_ID": "{env:OGM_PROJECT_ID}",
"OGM_PERMISSION_PROFILE": "{env:OGM_PERMISSION_PROFILE}"
},
"enabled": true
}
}
}
Restart OpenCode after editing config.
Hermes
Add server under mcp_servers:
mcp_servers:
ogm:
command: "uvx"
args:
- "ogm-mcp-skills==0.2.3"
env:
OGM_BASE_URL: "${OGM_BASE_URL}"
OGM_API_KEY: "${OGM_API_KEY}"
OGM_PROJECT_ID: "${OGM_PROJECT_ID}"
OGM_PERMISSION_PROFILE: "${OGM_PERMISSION_PROFILE}"
enabled: true
Verify:
hermes mcp test ogm
For source development, replace uvx ogm-mcp-skills==0.2.1 with:
uv run --project /absolute/path/ogm-mcp-skills ogm-mcp-skills
MCP uses stdio. Diagnostics go to stderr.
Use
After MCP server is connected, ask your agent to use OGM tools. Start with health and dataset discovery:
Call ogm_health, then ogm_list_datasets.
Search entities in one dataset:
{"dataset_id":"dataset-id","q":"OpenGraphMemory","limit":10}
Inspect graph context with ogm_get_entity, ogm_get_neighbors, ogm_get_subgraph, ogm_get_graph, or ogm_find_path. Use ogm_get_relation_evidence or ogm_get_evidence before making evidence-backed claims.
Retrieve relevant operational experience with ogm_memory_search. Create an episode, append attempts, and record a verified outcome only when profile is personal-safe. Feedback and supersession require memory-curator.
Upload documents only when profile is personal-safe and file path is under OGM_UPLOAD_ROOTS:
Call ogm_upload_document with an approved local file path and dataset/project context.
More Docs
Performance & Token Economics
The MCP server acts as an efficient bridge, converting broad file exploration queries into compact, structured graph and memory payloads:
| Workload | Raw LLM Context Dump | OGM MCP Structured Payload | Measured Reduction |
|---|---|---|---|
| Codebase Symbol Lookup | ~40k–80k tokens (reading entire folders) | ~500–1.5k tokens (ogm_get_code_call_graph) |
~90%–95% |
| Known Bug / Solution Recall | ~60k–150k tokens (3–5 turn trial & error) | ~1.5k–3k tokens (ogm_recall_code_memory) |
~75%–90% |
| Single-File Codebase Sync | Full repo re-index | ~10ms delta AST sync (ogm_sync_code_file) |
Instant |
[!NOTE] Token savings apply to repeated patterns, call-graph explorations, and known incident remediations. Unprecedented architectural problems still require exploratory reasoning, but newly verified solutions are immediately preserved for zero-overhead future retrieval.
Validation
uv sync --dev --locked
uv run ruff format --check .
uv run ruff check .
uv run mypy src
uv run pytest -q
uv build
Security
Use project-scoped keys. Keep .env and keys outside upload roots. Start read-only; use personal-safe only for reviewed writes; reserve memory-curator for memory governance. See security.
License
MIT. See LICENSE.
README fetched from the repository 10 hours ago. The original is authoritative.