Salesforce AgentForce CKG
PYPI · CKG-AGENTFORCE · 2 COMPONENTS · SCANNED SEP 20
Salesforce AgentForce knowledge graph — 40 nodes, Einstein Trust Layer, 11x fewer tokens than RAG.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 0 of 32 dependencies flagged as unhealthy. View diagnostics → Pass
Provenance & Transparency19
- Repository check failed: the declared repository URL returned HTTP 404. See how to fix → View diagnostics → Fail
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 48 days ago).Pass
- Security-disclosure policy not yet verified: we couldn't inspect the source repository.Unverified
Schema Quality & AI Usability86
- 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 1224 tokens (~111/item across 11 items; 9 tools + 2 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management87
- Stability observed for 26 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 9 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 11 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
How do I install the Salesforce AgentForce CKG MCP server?
Salesforce AgentForce CKG runs locally as a PyPI package, launched with uvx ckg-agentforce. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · ckg-agentforce
claude mcp add yarmoluk-ckg-agentforce -- uvx ckg-agentforce
{
"mcpServers": {
"yarmoluk-ckg-agentforce": {
"command": "uvx",
"args": [
"ckg-agentforce"
]
}
}
} {
"servers": {
"yarmoluk-ckg-agentforce": {
"command": "uvx",
"args": [
"ckg-agentforce"
]
}
}
} codex mcp add yarmoluk-ckg-agentforce -- uvx ckg-agentforce
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"yarmoluk-ckg-agentforce": {
"type": "local",
"command": [
"uvx",
"ckg-agentforce"
],
"enabled": true
}
}
} openclaw mcp add yarmoluk-ckg-agentforce --command uvx --arg ckg-agentforce
mcp_servers:
yarmoluk-ckg-agentforce:
command: "uvx"
args: ["ckg-agentforce"] {
"McpServers": {
"yarmoluk-ckg-agentforce": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"ckg-agentforce"
]
}
}
} assistant mcp add yarmoluk-ckg-agentforce -t stdio -c uvx -a ckg-agentforce
{
"mcpServers": {
"yarmoluk-ckg-agentforce": {
"command": "uvx",
"args": [
"ckg-agentforce"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 19 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.
- 18 Sept 26 −3
- Stability: pass → 0.80 functional
- 17 Sept 26 0
- Stability: 0.97 → pass security
- 16 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 93 to 97. That category is still filling its 30-day observation window: 28 days of observed history at the previous scan, 29 at this one. The score rises as the window fills, whether or not the server changes.
- 14 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 87 to 90. That category is still filling its 30-day observation window: 26 days of observed history at the previous scan, 27 at this one. The score rises as the window fills, whether or not the server changes.
- 12 Sept 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 80 to 83. That category is still filling its 30-day observation window: 24 days of observed history at the previous scan, 25 at this one. The score rises as the window fills, whether or not the server changes.
- 11 Sept 26 −3
- Stability: pass → 0.80 functional
- 10 Sept 26 0
- Stability: 0.97 → pass security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 20 Sept 2026 · Analysed pypi/ckg-agentforce@0.10.3
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 32 packages
| Packages resolved | 32 |
|---|---|
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
evaluate_trust_chain ~205
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).
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
export_benchmark_receipt ~119
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).
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
get_prerequisites ~72
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'.
| Name | Type | Req | Description |
|---|---|---|---|
| concept | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
list_concepts ~21
List all 40 AgentForce concepts in this knowledge graph.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
query_ckg ~112
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).
| Name | Type | Req | Description |
|---|---|---|---|
| concept | string | yes | – |
| depth | integer | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
resolution_path ~47
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.
Input schema present but exposes no named parameters.
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
route_query ~182
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.
| Name | Type | Req | Description |
|---|---|---|---|
| question | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
search_concepts ~51
Find AgentForce concepts by keyword. Args: query: Search term — e.g. 'resolution', 'trust', 'grounding', 'action', 'NIM'.
| Name | Type | Req | Description |
|---|---|---|---|
| query | string | yes | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
verify_source ~139
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.
| Name | Type | Req | Description |
|---|---|---|---|
| concept | string | yes | – |
| receipt | boolean | – | – |
| Name | Type | Req | Description |
|---|---|---|---|
| result | string | yes | – |
No examples provided.
What is the Salesforce AgentForce CKG MCP server?
Salesforce AgentForce CKG is an MCP server listed in the public MCP registry as io.github.Yarmoluk/ckg-agentforce. Salesforce AgentForce knowledge graph, 40 nodes, Einstein Trust Layer, 11x fewer tokens than RAG. This page covers its PyPI package (ckg-agentforce).
Is the Salesforce AgentForce CKG MCP server safe to use?
Salesforce AgentForce CKG scores 77 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Salesforce AgentForce CKG MCP server expose?
Salesforce AgentForce CKG exposes 9 tools: list_concepts, search_concepts, query_ckg, get_prerequisites, resolution_path, and 4 more. Their descriptions and schemas cost roughly 948 tokens of context every time the server is loaded.
Is the Salesforce AgentForce CKG MCP server still maintained?
Salesforce AgentForce CKG is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the Salesforce AgentForce CKG MCP server under?
Salesforce AgentForce CKG declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.