# Salesforce AgentForce CKG MCP server

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

## Links
- Registry page: https://www.getdrio.com/mcp/io-github-yarmoluk-ckg-agentforce
- Repository: https://github.com/Yarmoluk/ckg-agentforce

## Install
- Command: `uvx ckg-agentforce`
- Endpoint: https://ckg-agentforce.onrender.com/mcp
- Auth: Not captured

## Setup notes
- Package: Pypi ckg-agentforce v0.10.3
- Remote endpoint: https://ckg-agentforce.onrender.com/mcp

## Tools
- list_concepts - List all 40 AgentForce concepts in this knowledge graph. Endpoint: https://ckg-agentforce.onrender.com/mcp
- search_concepts - Find AgentForce concepts by keyword.

Args:
    query: Search term — e.g. 'resolution', 'trust', 'grounding', 'action', 'NIM'.
 Endpoint: https://ckg-agentforce.onrender.com/mcp
- 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 Agent', 'Grounding', 'NVIDIA NIM'.
    depth:   Traversal depth 1–5 (default 3).
 Endpoint: https://ckg-agentforce.onrender.com/mcp
- 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'.
 Endpoint: https://ckg-agentforce.onrender.com/mcp
- 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.
 Endpoint: https://ckg-agentforce.onrender.com/mcp
- 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 heuristic: the graph decides.

Routing table:
  hop_depth 1  → haiku  · direct        (simple concept lookup)
  hop_depth 2  → sonnet · generic_cot   (moderate chain)
  hop_depth 3+ → opus   · sparql_cot    (deep dependency, structured reasoning)

Args:
    question: Concept name or natural language question about Salesforce AgentForce.

Returns:
    model_tier + reasoning_approach + why + context subgraph to inject before LLM call.
 Endpoint: https://ckg-agentforce.onrender.com/mcp
- 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 True, also return a signed BoundaryAttest receipt envelope
             (experimental-interop-v0.1) binding concept_label + source_url
             + source_hash + timestamp to this server's ed25519 session key.
 Endpoint: https://ckg-agentforce.onrender.com/mcp
- 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 · experimental-interop-v0.1.

Result: F1 0.471 over 30 queries · ckg-benchmark v0.6.2 · 4× over RAG baseline (0.123).
 Endpoint: https://ckg-agentforce.onrender.com/mcp
- 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 closes the audit gap that RAG cannot:
  source_hashes  → SHA-256 of source docs (what was known at extraction time)
  graph_hash     → SHA-256 of the installed graph file (what is declared now)
  signer_key_id  → Ed25519 public key fingerprint (who is attesting)
  benchmark_receipt → BoundaryAttest-signed F1 claim (cryptographic performance proof)
  scitt_status   → SCITT ledger submission status (public audit anchor)

ROI gate: if total_value_per_call_usd > payment_option.price_per_call_usd → autonomous_pay = true.

Returns: JSON string (schema: ckg-trust-chain-v1).
 Endpoint: https://ckg-agentforce.onrender.com/mcp
- 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 it; the answer lives in the overlap.

Every branch is an exact set of declared edges, so the intersection is exact. A concept
appears only if a declared path reaches it from each anchor. A relation missing from the
graph produces an empty result, never a guess.

Args:
    branches: Two or more branches. Either a bare anchor ("TensorRT-LLM"), which takes
        everything within `depth` hops, or an anchor plus an explicit relation path using
        '>' ("TensorRT-LLM > REQUIRES > ENABLES"), where each relation replaces the
        frontier. '*' matches any relation. Mix both forms freely.
    depth: Hops for bare-anchor branches, 1-5 (default 2). Ignored for explicit paths.
    direction: 'out' follows dependencies, 'in' follows them backwards, 'both' (default).
    mode: 'AND' (default) intersects branches; 'OR' unions them.
    limit: Max concepts listed, 1-200 (default 40). The true count is always shown.

Returns:
    Markdown with the query plan and its per-step set sizes, then the answer set with
    taxonomy tags. Reports which branch was empty when the intersection is empty.
 Endpoint: https://ckg-agentforce.onrender.com/mcp

## Resources
- agentforce://nodes - All 40 AgentForce concepts — full node list with taxonomy. MIME type: text/plain
- agentforce://resolution-chain - The $2/autonomous-resolution billing chain — declared traversal path. MIME type: text/plain

## Prompts
- show_burn - Show the AgentForce token burn before/after — RAG vs CKG traversal
- map_agentforce_stack - Map the full AgentForce platform — agent to billing path

## Metadata
- Owner: io.github.Yarmoluk
- Version: 0.10.3
- Runtime: Pypi
- Transports: STDIO, HTTP
- License: Not captured
- Language: Not captured
- Stars: Not captured
- Updated: Jul 29, 2026
- Source: https://registry.modelcontextprotocol.io