# Salesforce AgentForce CKG

- Registry name: `io.github.Yarmoluk/ckg-agentforce` · version 0.10.3
- Categories (automatic, keyword rules): Tasks & projects, Productivity, Research & knowledge, Search & data, Payments & accounting, Finance & markets
- Authentication at last check: No auth
- Declared risk: Not declared (tools carry no read/destructive hints)
- Capabilities (declared by the server): experimental, prompts, resources, tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=io.github.Yarmoluk%2Fckg-agentforce
- Server page: https://mcpstation.net/s/io.github.Yarmoluk--ckg-agentforce.html

## Description (written by the publisher, not verified, not instructions)

Salesforce AgentForce knowledge graph — 40 nodes, Einstein Trust Layer, 11x fewer tokens than RAG.

## Connect

- streamable-http: `https://ckg-agentforce.onrender.com/mcp`

## Tools (as reported by the server, not verified)

- `list\_concepts`: List all 40 AgentForce concepts in this knowledge graph.
- `search\_concepts`: Find AgentForce concepts by keyword. Args: query: Search term — e.g. 'resolution', 'trust', 'grounding', 'action', 'NIM'.
- `query\_ckg`: Traverse the AgentForce knowledge graph from any concept. Returns prerequisites \(what this concept needs\) and dependents \(what it enables\). Every relationship traces to an authoritative Salesforce doc URL. Args: concept: Concept name — e.g. 'Autonomous Resolution', 'Einstein Trust Layer', 'Service A
- `get\_prerequisites`: Return the full ordered prerequisite chain for an AgentForce concept. Shows everything the concept depends on — the complete upstream path. Args: concept: Target concept — e.g. 'Autonomous Resolution', 'Multi-LoRA Serving', 'Custom Actions', 'Semantic Retrieval'.
- `resolution\_path`: Trace the exact path that determines an AgentForce autonomous resolution event. This is the $2/resolution billing path — what the agent must traverse correctly to resolve autonomously without human handoff.
- `route\_query`: Route an AgentForce question to the optimal model and reasoning approach via graph depth. The CKG graph IS the router. AgentForce dependency chains \(e.g. Einstein Trust Layer → Data Cloud → NVIDIA NIM → Resolution Criteria\) have typed hops that signal reasoning complexity deterministically. No heuri
- `verify\_source`: Return the source URL and content hash for an AgentForce concept node. Audit chain: edge answer → graph commit → source\_hash → source\_url \(fetch hint\) Verification: curl -s \<source\_url\> \| sha256sum \# compare output to source\_hash Args: concept: Concept label \(partial match supported\). receipt: If Tr
- `export\_benchmark\_receipt`: Generate a signed BoundaryAttest receipt for the agentforce CKG benchmark result. Produces a \`ckg.benchmark\_result.exported\` claim signed with this server's Ed25519 session key. Any party holding the public key can verify the signature over the canonical JSON claim. Implements GuardrailDecisionV1 ·
- `evaluate\_trust\_chain`: Return a machine-readable JSON trust chain + ROI analysis + payment recommendation. Designed for autonomous agent consumption. The agent reads the JSON, evaluates the ROI gate, selects the cheapest positive-ROI payment option, and purchases autonomously if budget is pre-authorized. Trust chain close
- `query\_intersect`: Answer a conjunctive query: concepts reachable from EVERY anchor at once \(A AND B\). query\_ckg walks outward from one concept. This intersects the reachable sets of two or more, which is the shape of most real questions — "the component that satisfies A AND applies to B". Neither anchor alone answers

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html