graphite-mcp
OfficialServer Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CUSTOMER_API_KEY | Yes | Your Graphite API key issued at https://graph.graphite-ai.net/#/portal | |
| CENTRAL_SERVER_URL | No | Override to use a different Graphite deployment | http://localhost:8000 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_entitiesB | Search the financial knowledge graph for companies, people, patents by name, ticker, or description. Example: search_entities(query='NVIDIA') or search_entities(query='semiconductor', sector='semiconductors') |
| get_entityA | Get detailed information about a specific entity by ID. Example: get_entity(entity_id='company:NVDA') |
| get_relationshipsB | Get all relationships for an entity — suppliers, competitors, partners, dependencies, etc. Example: get_relationships(entity_id='company:NVDA') |
| get_factsA | Get known facts about an entity — revenue, employee count, etc. Example: get_facts(entity_id='company:AAPL') |
| find_pathA | Find how two companies/entities are connected through the knowledge graph. Shows the chain of relationships. Example: find_path(source='company:AAPL', target='company:TSM') |
| exposure_analysisA | Analyze a company's exposure: 1st and 2nd degree connections, sector concentration, dependency risks. Example: exposure_analysis(entity_id='company:TSM') |
| compare_entitiesA | Compare two entities: shared connections, direct relationships, path distance. Example: compare_entities(entity_a='company:NVDA', entity_b='company:AMD') |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 7 tools
Each tool has a clearly distinct purpose: search, detail retrieval, relationship listing, fact retrieval, path finding, exposure analysis, and pairwise comparison. No two tools appear to do the same thing, and descriptions specify unique parameters and outputs. Even the two-entity tools (find_path and compare_entities) are differentiated by their focus on connection chains versus shared relationships.
Most tools follow a consistent snake_case verb_noun or verb_noun pattern (search_entities, get_entity, get_relationships, get_facts, find_path, compare_entities). The only slight deviation is exposure_analysis, which uses a noun phrase rather than a verb-prefixed form, but this is minor and does not create confusion.
Seven tools is an appropriate size for a specialized financial knowledge graph server. Each tool addresses a distinct query need without redundancy or bloat. This falls well within the ideal 3-15 range for a focused domain.
The tool surface covers the core lifecycle of knowledge graph exploration: search, retrieve entity details, list relationships, retrieve facts, trace paths, analyze exposure, and compare entities. There are no obvious missing operations for a read-only analytical server. All tools can be chained since they accept entity IDs returned by search or get operations.