MCP & Agent-to-Agent

McpClient exposes Relata as a governed MCP tool source: list_tools + call_tool, plus 72 typed tool wrappers. A2AClient is the agent-to-agent door: discover the agent card, submit tasks, persist checkpoints across runs.

71 methods across this domain. Signatures, parameters (incl. keyword-only tunable defaults), and the three SDK spellings are ported from the live SDK source; flagship methods carry a hand-written When to use + example.

`McpClient`

`call_tool(name, arguments=None)`

When to use. Invoke any of Relata's governed MCP tools by name with a JSON arg map.

Python — client.mcpclient.call_tool(name, arguments=None)
TypeScript — callTool(name, args)
Go — CallTool(name, arguments)

Parameters: name, arguments=None

Example

mcp = McpClient.from_client(relata)
print(mcp.call_tool("memory_search", {"query": "alice", "top_k": 3}))

`add_case_note(case_id, note, author=None)`

add_case_note(case_id, note, author=None)`

Python — client.mcpclient.add_case_note(case_id, note, author=None)
TypeScript — addCaseNote(caseId, note, opts)
Go — AddCaseNote(caseID, note)

Parameters: case_id, note, author=None

`aggregate_stats(entity_type, agg='COUNT', column='*', purpose='analytics')`

aggregate_stats(entity_type, agg='COUNT', column='*', purpose='analytics')`

Python — client.mcpclient.aggregate_stats(entity_type, agg='COUNT', column='*', purpose='analytics')
TypeScript — aggregateStats(entityType, opts)
Go — AggregateStats(entityType)

Parameters: entity_type, agg='COUNT', column='*', purpose='analytics'

`associate(from_id, to_id, relation='related_to', purpose=None)`

associate(from_id, to_id, relation='related_to', purpose=None)`

Python — client.mcpclient.associate(from_id, to_id, relation='related_to', purpose=None)
TypeScript — associate(fromId, toId, opts)
Go — Associate(fromID, toID)

Parameters: from_id, to_id, relation='related_to', purpose=None

`beneficial_ownership(party, max_depth=6, purpose='analytics')`

beneficial_ownership(party, max_depth=6, purpose='analytics')`

Python — client.mcpclient.beneficial_ownership(party, max_depth=6, purpose='analytics')
TypeScript — beneficialOwnership(party, opts)
Go — BeneficialOwnership(party)

Parameters: party, max_depth=6, purpose='analytics'

`consolidate(memory_id, content, confidence=1.0, purpose=None)`

consolidate(memory_id, content, confidence=1.0, purpose=None)`

Python — client.mcpclient.consolidate(memory_id, content, confidence=1.0, purpose=None)
TypeScript — consolidate(memoryId, content, opts)
Go — Consolidate(memoryID, content)

Parameters: memory_id, content, confidence=1.0, purpose=None

`create_rule(name, condition_sql, severity=None, description=None, purpose='security')`

create_rule(name, condition_sql, severity=None, description=None, purpose='security')`

Python — client.mcpclient.create_rule(name, condition_sql, severity=None, description=None, purpose='security')
TypeScript — createRule(name, conditionSql, opts)
Go — CreateRule(name, conditionSQL)

Parameters: name, condition_sql, severity=None, description=None, purpose='security'

`detect_communities(entity_type, algo='louvain', purpose='analytics')`

detect_communities(entity_type, algo='louvain', purpose='analytics')`

Python — client.mcpclient.detect_communities(entity_type, algo='louvain', purpose='analytics')
TypeScript — detectCommunities(entityType, opts)
Go — DetectCommunities(entityType)

Parameters: entity_type, algo='louvain', purpose='analytics'

`episodes_in(session_id, limit=20, purpose=None)`

episodes_in(session_id, limit=20, purpose=None)`

Python — client.mcpclient.episodes_in(session_id, limit=20, purpose=None)
TypeScript — episodesIn(sessionId, opts)
Go — EpisodesIn(sessionID)

Parameters: session_id, limit=20, purpose=None

`erase_subject(subject, reason='gdpr-art17-request')`

erase_subject(subject, reason='gdpr-art17-request')`

Python — client.mcpclient.erase_subject(subject, reason='gdpr-art17-request')
TypeScript — eraseSubject(subject, opts)
Go — EraseSubject(subject)

Parameters: subject, reason='gdpr-art17-request'

`explain_policy(sql, purpose)`

explain_policy(sql, purpose)`

Python — client.mcpclient.explain_policy(sql, purpose)
TypeScript — explainPolicy(sql, purpose)
Go — ExplainPolicy(sql, purpose)

Parameters: sql, purpose

`face_match(probe_id, threshold=0.8, top_k=10, purpose='security_incident')`

face_match(probe_id, threshold=0.8, top_k=10, purpose='security_incident')`

Python — client.mcpclient.face_match(probe_id, threshold=0.8, top_k=10, purpose='security_incident')
TypeScript — faceMatch(probeId, opts)
Go — FaceMatch(probeID)

Parameters: probe_id, threshold=0.8, top_k=10, purpose='security_incident'

`find_connections(entity, purpose, limit=50)`

find_connections(entity, purpose, limit=50)`

Python — client.mcpclient.find_connections(entity, purpose, limit=50)
TypeScript — findConnections(entity, purpose, opts)
Go — FindConnections(entity, purpose)

Parameters: entity, purpose, limit=50

`find_in_social_corpus(object_type, text_query=None, user=None, top_k=20)`

find_in_social_corpus(object_type, text_query=None, user=None, top_k=20)`

Python — client.mcpclient.find_in_social_corpus(object_type, text_query=None, user=None, top_k=20)
TypeScript — findInSocialCorpus(query, opts)
Go — FindInSocialCorpus(query)

Parameters: object_type, text_query=None, user=None, top_k=20

`find_scc(entity_type, purpose='analytics')`

find_scc(entity_type, purpose='analytics')`

Python — client.mcpclient.find_scc(entity_type, purpose='analytics')
TypeScript — findScc(entityType, opts)
Go — FindScc(entityType, purpose)

Parameters: entity_type, purpose='analytics'

`find_threats(entity_type, purpose='security_incident')`

find_threats(entity_type, purpose='security_incident')`

Python — client.mcpclient.find_threats(entity_type, purpose='security_incident')
TypeScript — findThreats(entityType, opts)
Go — FindThreats(entityType, purpose)

Parameters: entity_type, purpose='security_incident'

`forget(memory_id, retain_days=0, purpose=None)`

forget(memory_id, retain_days=0, purpose=None)`

Python — client.mcpclient.forget(memory_id, retain_days=0, purpose=None)
TypeScript — forget(memoryId, opts)
Go — Forget(memoryID)

Parameters: memory_id, retain_days=0, purpose=None

`geofence(lat, lon, radius_m=1000, target_type='MovementEvent', purpose='analytics')`

geofence(lat, lon, radius_m=1000, target_type='MovementEvent', purpose='analytics')`

Python — client.mcpclient.geofence(lat, lon, radius_m=1000, target_type='MovementEvent', purpose='analytics')
TypeScript — geofence(lat, lon, opts)
Go — Geofence(lat, lon)

Parameters: lat, lon, radius_m=1000, target_type='MovementEvent', purpose='analytics'

`get_audit_trail(purpose=None, principal_filter=None, limit=100)`

get_audit_trail(purpose=None, principal_filter=None, limit=100)`

Python — client.mcpclient.get_audit_trail(purpose=None, principal_filter=None, limit=100)
TypeScript — getAuditTrail(opts)
Go — GetAuditTrail()

Parameters: purpose=None, principal_filter=None, limit=100

`get_case_summary(case_id, purpose)`

get_case_summary(case_id, purpose)`

Python — client.mcpclient.get_case_summary(case_id, purpose)
TypeScript — getCaseSummary(caseId, purpose)
Go — GetCaseSummary(caseID, purpose)

Parameters: case_id, purpose

`get_domain_summary(domain)`

get_domain_summary(domain)`

Python — client.mcpclient.get_domain_summary(domain)
TypeScript — getDomainSummary(opts)
Go — GetDomainSummary(domain)

Parameters: domain

`get_entities(object_type, filters=None, limit=50)`

get_entities(object_type, filters=None, limit=50)`

Python — client.mcpclient.get_entities(object_type, filters=None, limit=50)
TypeScript — getEntities(objectType, opts)
Go — GetEntities(objectType)

Parameters: object_type, filters=None, limit=50

`get_entity_profile(entity_id, purpose)`

get_entity_profile(entity_id, purpose)`

Python — client.mcpclient.get_entity_profile(entity_id, purpose)
TypeScript — getEntityProfile(entityId, purpose)
Go — GetEntityProfile(entityID, purpose)

Parameters: entity_id, purpose

`get_relationships(subject=None, purpose, predicate=None, object=None, source=None, limit=50)`

get_relationships(subject=None, purpose, predicate=None, object=None, source=None, limit=50)`

Python — client.mcpclient.get_relationships(subject=None, purpose, predicate=None, object=None, source=None, limit=50)
TypeScript — getRelationships(entityId, purpose, opts)
Go — GetRelationships(entityID, purpose)

Parameters: subject=None, purpose, predicate=None, object=None, source=None, limit=50

`get_timeline(entity_id, purpose, since_ns=None, until_ns=None)`

get_timeline(entity_id, purpose, since_ns=None, until_ns=None)`

Python — client.mcpclient.get_timeline(entity_id, purpose, since_ns=None, until_ns=None)
TypeScript — getTimeline(entityId, purpose, opts)
Go — GetTimeline(entityID, purpose)

Parameters: entity_id, purpose, since_ns=None, until_ns=None

`hub_authority(entity_type, max_iter=20, purpose='analytics')`

hub_authority(entity_type, max_iter=20, purpose='analytics')`

Python — client.mcpclient.hub_authority(entity_type, max_iter=20, purpose='analytics')
TypeScript — hubAuthority(entityType, opts)
Go — HubAuthority(entityType)

Parameters: entity_type, max_iter=20, purpose='analytics'

`hybrid_search(entity_type, query, top_k=10, purpose=None)`

hybrid_search(entity_type, query, top_k=10, purpose=None)`

Python — client.mcpclient.hybrid_search(entity_type, query, top_k=10, purpose=None)
TypeScript — hybridSearch(entityType, query, opts)
Go — HybridSearch(entityType, query)

Parameters: entity_type, query, top_k=10, purpose=None

`import_sigma(sigma_yaml, purpose='security')`

import_sigma(sigma_yaml, purpose='security')`

Python — client.mcpclient.import_sigma(sigma_yaml, purpose='security')
TypeScript — importSigma(sigmaYaml, opts)
Go — ImportSigma(sigmaYAML, purpose)

Parameters: sigma_yaml, purpose='security'

`ingest_document(chunks_jsonl, manifest_json, purpose)`

ingest_document(chunks_jsonl, manifest_json, purpose)`

Python — client.mcpclient.ingest_document(chunks_jsonl, manifest_json, purpose)
TypeScript — ingestDocument(chunksJsonl, manifestJson, purpose)
Go — IngestDocument(chunksJSONL, manifestJSON, purpose)

Parameters: chunks_jsonl, manifest_json, purpose

`ingest_media(object_type, modality='image', codec=None, bytes_b64=None, text=None, tenant_id=None, partition_key=None)`

ingest_media(object_type, modality='image', codec=None, bytes_b64=None, text=None, tenant_id=None, partition_key=None)`

Python — client.mcpclient.ingest_media(object_type, modality='image', codec=None, bytes_b64=None, text=None, tenant_id=None, partition_key=None)
TypeScript — ingestMedia(objectType, opts)
Go — IngestMedia(objectType)

Parameters: object_type, modality='image', codec=None, bytes_b64=None, text=None, tenant_id=None, partition_key=None

`initialize(client_id='relata-python-sdk', version='1.0')`

initialize(client_id='relata-python-sdk', version='1.0')`

Python — client.mcpclient.initialize(client_id='relata-python-sdk', version='1.0')
TypeScript — initialize(opts)
Go — Initialize()

Parameters: client_id='relata-python-sdk', version='1.0'

`investigate_entity(entity_type, entity_id, purpose='security_incident')`

investigate_entity(entity_type, entity_id, purpose='security_incident')`

Python — client.mcpclient.investigate_entity(entity_type, entity_id, purpose='security_incident')
TypeScript — investigateEntity(entityType, entityId, opts)
Go — InvestigateEntity(entityType, entityID, purpose)

Parameters: entity_type, entity_id, purpose='security_incident'

`job_status()`

job_status()`

Python — client.mcpclient.job_status()
TypeScript — jobStatus()
Go — JobStatus()

`justify(memory_id, purpose=None)`

justify(memory_id, purpose=None)`

Python — client.mcpclient.justify(memory_id, purpose=None)
TypeScript — justify(memoryId, opts)
Go — Justify(memoryID, purpose)

Parameters: memory_id, purpose=None

`list_entity_types()`

list_entity_types()`

Python — client.mcpclient.list_entity_types()
TypeScript — listEntityTypes()
Go — ListEntityTypes()

`list_jobs()`

list_jobs()`

Python — client.mcpclient.list_jobs()
TypeScript — listJobs()
Go — ListJobs()

`list_link_types()`

list_link_types()`

Python — client.mcpclient.list_link_types()
TypeScript — listLinkTypes()
Go — ListLinkTypes()

`list_rules()`

list_rules()`

Python — client.mcpclient.list_rules()
TypeScript — listRules()
Go — ListRules()

`list_tools()`

list_tools()`

Python — client.mcpclient.list_tools()
TypeScript — listTools()
Go — ListTools()

`list_workflows()`

list_workflows()`

Python — client.mcpclient.list_workflows()
TypeScript — listWorkflows()
Go — ListWorkflows()

`lookup_identity(value, purpose='analytics')`

lookup_identity(value, purpose='analytics')`

Python — client.mcpclient.lookup_identity(value, purpose='analytics')
TypeScript — lookupIdentity(value, opts)
Go — LookupIdentity(value)

Parameters: value, purpose='analytics'

`metrics()`

metrics()`

Python — client.mcpclient.metrics()
TypeScript — metrics()
Go — Metrics()

`nl_query(query, purpose=None, interpret=False, max_sub_questions=None)`

nl_query(query, purpose=None, interpret=False, max_sub_questions=None)`

Python — client.mcpclient.nl_query(query, purpose=None, interpret=False, max_sub_questions=None)
TypeScript — nlQuery(query, opts)
Go — NlQuery(query)

Parameters: query, purpose=None, interpret=False, max_sub_questions=None

A dialect router classifies each question as SQL, Cypher, or a governed graph operator (PATHS_BETWEEN / GRAPH_DIJKSTRA / GRAPH_COMMUNITY / IDENTITY_PATH / BENEFICIAL_OWNERSHIP_CHAIN / SANCTIONS_SCREEN) and prompts accordingly — the response carries a dialect field. Pass max_sub_questions (capped at 5) to decompose a multi-part question — e.g. "find John Smith, and who he is linked to" — into independently-routed, independently-executed sub-questions; the response then carries decomposed: true and a sub_results array instead of a single result. Omitted or 1, the response shape is unchanged.

`paths_between(from_id, to_id, max_hops=4, purpose=None)`

paths_between(from_id, to_id, max_hops=4, purpose=None)`

Python — client.mcpclient.paths_between(from_id, to_id, max_hops=4, purpose=None)
TypeScript — pathsBetween(fromId, toId, opts)
Go — PathsBetween(fromID, toID)

Parameters: from_id, to_id, max_hops=4, purpose=None

`predict_links(entity_type, from_id=None, to_id=None, method='common_neighbors', purpose='analytics')`

predict_links(entity_type, from_id=None, to_id=None, method='common_neighbors', purpose='analytics')`

Python — client.mcpclient.predict_links(entity_type, from_id=None, to_id=None, method='common_neighbors', purpose='analytics')
TypeScript — predictLinks(entityType, opts)
Go — PredictLinks(entityType)

Parameters: entity_type, from_id=None, to_id=None, method='common_neighbors', purpose='analytics'

`query_knowledge(sql, purpose)`

query_knowledge(sql, purpose)`

Python — client.mcpclient.query_knowledge(sql, purpose)
TypeScript — queryKnowledge(sql, purpose)
Go — QueryKnowledge(sql, purpose)

Parameters: sql, purpose

`rag_store_answer(question, answer, source_ids=None, purpose)`

rag_store_answer(question, answer, source_ids=None, purpose)`

Python — client.mcpclient.rag_store_answer(question, answer, source_ids=None, purpose)
TypeScript — ragStoreAnswer(question, answer, purpose, opts)
Go — RagStoreAnswer(question, answer, purpose)

Parameters: question, answer, source_ids=None, purpose

`rag_store_elements(elements, purpose)`

rag_store_elements(elements, purpose)`

Python — client.mcpclient.rag_store_elements(elements, purpose)
TypeScript — ragStoreElements(elements, purpose)
Go — RagStoreElements(elements, sourceFilename, purpose)

Parameters: elements, purpose

`rank_key_nodes(entity_type, metric='pagerank', damping=0.85, max_iter=20, purpose='analytics')`

rank_key_nodes(entity_type, metric='pagerank', damping=0.85, max_iter=20, purpose='analytics')`

Python — client.mcpclient.rank_key_nodes(entity_type, metric='pagerank', damping=0.85, max_iter=20, purpose='analytics')
TypeScript — rankKeyNodes(entityType, opts)
Go — RankKeyNodes(entityType)

Parameters: entity_type, metric='pagerank', damping=0.85, max_iter=20, purpose='analytics'

`recall(query, purpose, top_k=5, min_confidence=None, recency_half_life_secs=None, budget_tokens=None, stability_days=None, cancel_threshold=None)`

recall(query, purpose, top_k=5, min_confidence=None, recency_half_life_secs=None, budget_tokens=None, stability_days=None, cancel_threshold=None)`

Python — client.mcpclient.recall(query, purpose, top_k=5, min_confidence=None, recency_half_life_secs=None, budget_tokens=None, stability_days=None, cancel_threshold=None)
TypeScript — recall(query, purpose, opts)
Go — Recall(query, purpose)

Parameters: query, purpose, top_k=5, min_confidence=None, recency_half_life_secs=None, budget_tokens=None, stability_days=None, cancel_threshold=None

`recall_procedure(agent_id, name=None, all_versions=False, limit=20, purpose=None)`

recall_procedure(agent_id, name=None, all_versions=False, limit=20, purpose=None)`

Python — client.mcpclient.recall_procedure(agent_id, name=None, all_versions=False, limit=20, purpose=None)
TypeScript — recallProcedure(agentId, opts)
Go — RecallProcedure(agentID)

Parameters: agent_id, name=None, all_versions=False, limit=20, purpose=None

`recognize(memory_id, purpose=None)`

recognize(memory_id, purpose=None)`

Python — client.mcpclient.recognize(memory_id, purpose=None)
TypeScript — recognize(memoryId, opts)
Go — Recognize(memoryID, purpose)

Parameters: memory_id, purpose=None

`reconstruct_wire(account, tolerance_pct=5.0, purpose='analytics')`

reconstruct_wire(account, tolerance_pct=5.0, purpose='analytics')`

Python — client.mcpclient.reconstruct_wire(account, tolerance_pct=5.0, purpose='analytics')
TypeScript — reconstructWire(account, opts)
Go — ReconstructWire(account)

Parameters: account, tolerance_pct=5.0, purpose='analytics'

`remember(content, purpose, confidence=1.0, memory_class='semantic')`

remember(content, purpose, confidence=1.0, memory_class='semantic')`

Python — client.mcpclient.remember(content, purpose, confidence=1.0, memory_class='semantic')
TypeScript — remember(content, purpose, opts)
Go — Remember(content, purpose)

Parameters: content, purpose, confidence=1.0, memory_class='semantic'

`remember_batch(items, purpose=None)`

remember_batch(items, purpose=None)`

Python — client.mcpclient.remember_batch(items, purpose=None)
TypeScript — rememberBatch(items, opts)
Go — RememberBatch(items)

Parameters: items, purpose=None

`remember_procedure(agent_id, name, instruction_text, purpose=None)`

remember_procedure(agent_id, name, instruction_text, purpose=None)`

Python — client.mcpclient.remember_procedure(agent_id, name, instruction_text, purpose=None)
TypeScript — rememberProcedure(agentId, name, instructionText, opts)
Go — RememberProcedure(agentID, name, instructionText, purpose)

Parameters: agent_id, name, instruction_text, purpose=None

`resolve(memory_id, purpose=None)`

resolve(memory_id, purpose=None)`

Python — client.mcpclient.resolve(memory_id, purpose=None)
TypeScript — resolve(memoryId, opts)
Go — Resolve(memoryID, purpose)

Parameters: memory_id, purpose=None

`resolve_entity_identity(identity, purpose='analytics')`

resolve_entity_identity(identity, purpose='analytics')`

Python — client.mcpclient.resolve_entity_identity(identity, purpose='analytics')
TypeScript — resolveEntityIdentity(identity, opts)
Go — ResolveEntityIdentity(identity, purpose)

Parameters: identity, purpose='analytics'

`run_workflow(name)`

run_workflow(name)`

Python — client.mcpclient.run_workflow(name)
TypeScript — runWorkflow(name)
Go — RunWorkflow(name)

Parameters: name

`schedule_job(name)`

schedule_job(name)`

Python — client.mcpclient.schedule_job(name)
TypeScript — scheduleJob(name)
Go — ScheduleJob(name)

Parameters: name

`screen_sanctions(name, threshold=None, purpose='compliance_review')`

screen_sanctions(name, threshold=None, purpose='compliance_review')`

Python — client.mcpclient.screen_sanctions(name, threshold=None, purpose='compliance_review')
TypeScript — screenSanctions(name, opts)
Go — ScreenSanctions(name)

Parameters: name, threshold=None, purpose='compliance_review'

`search_entities(query, entity_types=None)`

search_entities(query, entity_types=None)`

Python — client.mcpclient.search_entities(query, entity_types=None)
TypeScript — searchEntities(query, opts)
Go — SearchEntities(query)

Parameters: query, entity_types=None

`search_knowledge(query, purpose, top_k=10)`

search_knowledge(query, purpose, top_k=10)`

Python — client.mcpclient.search_knowledge(query, purpose, top_k=10)
TypeScript — searchKnowledge(query, purpose, opts)
Go — SearchKnowledge(query, purpose, topK)

Parameters: query, purpose, top_k=10

`search_video_frames(query_id, media_type='VideoFrame', top_k=20, purpose='security_incident')`

search_video_frames(query_id, media_type='VideoFrame', top_k=20, purpose='security_incident')`

Python — client.mcpclient.search_video_frames(query_id, media_type='VideoFrame', top_k=20, purpose='security_incident')
TypeScript — searchVideoFrames(queryId, opts)
Go — SearchVideoFrames(queryID)

Parameters: query_id, media_type='VideoFrame', top_k=20, purpose='security_incident'

`server_health()`

server_health()`

Python — client.mcpclient.server_health()
TypeScript — serverHealth()
Go — ServerHealth()

`similar_multimodal(entity_type, entity_id, top_k=10, modality='text', purpose=None)`

similar_multimodal(entity_type, entity_id, top_k=10, modality='text', purpose=None)`

Python — client.mcpclient.similar_multimodal(entity_type, entity_id, top_k=10, modality='text', purpose=None)
TypeScript — similarMultimodal(entityType, entityId, opts)
Go — SimilarMultimodal(entityType, entityID)

Parameters: entity_type, entity_id, top_k=10, modality='text', purpose=None

`suggest_extensions(prefix)`

suggest_extensions(prefix)`

Python — client.mcpclient.suggest_extensions()
TypeScript — suggestExtensions(prefix)
Go — SuggestExtensions(prefix)

Parameters: prefix

`summarise(ids=None, session_id=None, scope=None, contents=None, purpose=None)`

summarise(ids=None, session_id=None, scope=None, contents=None, purpose=None)`

Python — client.mcpclient.summarise(ids=None, session_id=None, scope=None, contents=None, purpose=None)
TypeScript — summarise(opts)
Go — Summarise()

Parameters: ids=None, session_id=None, scope=None, contents=None, purpose=None

`trace_crypto(address, max_hops=5, min_amount=0, purpose='analytics')`

trace_crypto(address, max_hops=5, min_amount=0, purpose='analytics')`

Python — client.mcpclient.trace_crypto(address, max_hops=5, min_amount=0, purpose='analytics')
TypeScript — traceCrypto(address, opts)
Go — TraceCrypto(address)

Parameters: address, max_hops=5, min_amount=0, purpose='analytics'

`trace_hawala(seed, max_hops=5, purpose='analytics')`

trace_hawala(seed, max_hops=5, purpose='analytics')`

Python — client.mcpclient.trace_hawala(seed, max_hops=5, purpose='analytics')
TypeScript — traceHawala(seed, opts)
Go — TraceHawala(seed)

Parameters: seed, max_hops=5, purpose='analytics'

`workflow_status(run_id)`

workflow_status(run_id)`

Python — client.mcpclient.workflow_status(run_id)
TypeScript — workflowStatus(runId)
Go — WorkflowStatus(runID)

Parameters: run_id

MCP & Agent-to-Agent#

McpClient#

call_tool(name, arguments=None)#

add_case_note(case_id, note, author=None)#

aggregate_stats(entity_type, agg='COUNT', column='*', purpose='analytics')#

associate(from_id, to_id, relation='related_to', purpose=None)#

beneficial_ownership(party, max_depth=6, purpose='analytics')#

consolidate(memory_id, content, confidence=1.0, purpose=None)#

create_rule(name, condition_sql, severity=None, description=None, purpose='security')#

detect_communities(entity_type, algo='louvain', purpose='analytics')#

episodes_in(session_id, limit=20, purpose=None)#

erase_subject(subject, reason='gdpr-art17-request')#

explain_policy(sql, purpose)#

face_match(probe_id, threshold=0.8, top_k=10, purpose='security_incident')#

find_connections(entity, purpose, limit=50)#

find_in_social_corpus(object_type, text_query=None, user=None, top_k=20)#

find_scc(entity_type, purpose='analytics')#

find_threats(entity_type, purpose='security_incident')#

forget(memory_id, retain_days=0, purpose=None)#

geofence(lat, lon, radius_m=1000, target_type='MovementEvent', purpose='analytics')#

get_audit_trail(purpose=None, principal_filter=None, limit=100)#

get_case_summary(case_id, purpose)#

get_domain_summary(domain)#

get_entities(object_type, filters=None, limit=50)#

get_entity_profile(entity_id, purpose)#

get_relationships(subject=None, purpose, predicate=None, object=None, source=None, limit=50)#

get_timeline(entity_id, purpose, since_ns=None, until_ns=None)#

hub_authority(entity_type, max_iter=20, purpose='analytics')#

hybrid_search(entity_type, query, top_k=10, purpose=None)#

import_sigma(sigma_yaml, purpose='security')#

ingest_document(chunks_jsonl, manifest_json, purpose)#

ingest_media(object_type, modality='image', codec=None, bytes_b64=None, text=None, tenant_id=None, partition_key=None)#

initialize(client_id='relata-python-sdk', version='1.0')#

investigate_entity(entity_type, entity_id, purpose='security_incident')#

job_status()#

justify(memory_id, purpose=None)#

list_entity_types()#

list_jobs()#

list_link_types()#

list_rules()#

list_tools()#

list_workflows()#

lookup_identity(value, purpose='analytics')#

metrics()#

nl_query(query, purpose=None, interpret=False, max_sub_questions=None)#

paths_between(from_id, to_id, max_hops=4, purpose=None)#

predict_links(entity_type, from_id=None, to_id=None, method='common_neighbors', purpose='analytics')#

query_knowledge(sql, purpose)#

rag_store_answer(question, answer, source_ids=None, purpose)#

rag_store_elements(elements, purpose)#

rank_key_nodes(entity_type, metric='pagerank', damping=0.85, max_iter=20, purpose='analytics')#

recall(query, purpose, top_k=5, min_confidence=None, recency_half_life_secs=None, budget_tokens=None, stability_days=None, cancel_threshold=None)#

recall_procedure(agent_id, name=None, all_versions=False, limit=20, purpose=None)#

recognize(memory_id, purpose=None)#

reconstruct_wire(account, tolerance_pct=5.0, purpose='analytics')#

remember(content, purpose, confidence=1.0, memory_class='semantic')#

remember_batch(items, purpose=None)#

remember_procedure(agent_id, name, instruction_text, purpose=None)#

resolve(memory_id, purpose=None)#

resolve_entity_identity(identity, purpose='analytics')#

run_workflow(name)#

schedule_job(name)#

screen_sanctions(name, threshold=None, purpose='compliance_review')#

search_entities(query, entity_types=None)#

search_knowledge(query, purpose, top_k=10)#

search_video_frames(query_id, media_type='VideoFrame', top_k=20, purpose='security_incident')#

server_health()#

similar_multimodal(entity_type, entity_id, top_k=10, modality='text', purpose=None)#

suggest_extensions(prefix)#

summarise(ids=None, session_id=None, scope=None, contents=None, purpose=None)#

trace_crypto(address, max_hops=5, min_amount=0, purpose='analytics')#

trace_hawala(seed, max_hops=5, purpose='analytics')#

workflow_status(run_id)#

MCP & Agent-to-Agent

`McpClient`

`call_tool(name, arguments=None)`

`add_case_note(case_id, note, author=None)`

`aggregate_stats(entity_type, agg='COUNT', column='*', purpose='analytics')`

`associate(from_id, to_id, relation='related_to', purpose=None)`

`beneficial_ownership(party, max_depth=6, purpose='analytics')`

`consolidate(memory_id, content, confidence=1.0, purpose=None)`

`create_rule(name, condition_sql, severity=None, description=None, purpose='security')`

`detect_communities(entity_type, algo='louvain', purpose='analytics')`

`episodes_in(session_id, limit=20, purpose=None)`

`erase_subject(subject, reason='gdpr-art17-request')`

`explain_policy(sql, purpose)`

`face_match(probe_id, threshold=0.8, top_k=10, purpose='security_incident')`

`find_connections(entity, purpose, limit=50)`

`find_in_social_corpus(object_type, text_query=None, user=None, top_k=20)`

`find_scc(entity_type, purpose='analytics')`

`find_threats(entity_type, purpose='security_incident')`

`forget(memory_id, retain_days=0, purpose=None)`

`geofence(lat, lon, radius_m=1000, target_type='MovementEvent', purpose='analytics')`

`get_audit_trail(purpose=None, principal_filter=None, limit=100)`

`get_case_summary(case_id, purpose)`

`get_domain_summary(domain)`

`get_entities(object_type, filters=None, limit=50)`

`get_entity_profile(entity_id, purpose)`

`get_relationships(subject=None, purpose, predicate=None, object=None, source=None, limit=50)`

`get_timeline(entity_id, purpose, since_ns=None, until_ns=None)`

`hub_authority(entity_type, max_iter=20, purpose='analytics')`

`hybrid_search(entity_type, query, top_k=10, purpose=None)`

`import_sigma(sigma_yaml, purpose='security')`

`ingest_document(chunks_jsonl, manifest_json, purpose)`

`ingest_media(object_type, modality='image', codec=None, bytes_b64=None, text=None, tenant_id=None, partition_key=None)`

`initialize(client_id='relata-python-sdk', version='1.0')`

`investigate_entity(entity_type, entity_id, purpose='security_incident')`

`job_status()`

`justify(memory_id, purpose=None)`

`list_entity_types()`

`list_jobs()`

`list_link_types()`

`list_rules()`

`list_tools()`

`list_workflows()`

`lookup_identity(value, purpose='analytics')`

`metrics()`

`nl_query(query, purpose=None, interpret=False, max_sub_questions=None)`

`paths_between(from_id, to_id, max_hops=4, purpose=None)`

`predict_links(entity_type, from_id=None, to_id=None, method='common_neighbors', purpose='analytics')`

`query_knowledge(sql, purpose)`

`rag_store_answer(question, answer, source_ids=None, purpose)`

`rag_store_elements(elements, purpose)`

`rank_key_nodes(entity_type, metric='pagerank', damping=0.85, max_iter=20, purpose='analytics')`

`recall(query, purpose, top_k=5, min_confidence=None, recency_half_life_secs=None, budget_tokens=None, stability_days=None, cancel_threshold=None)`

`recall_procedure(agent_id, name=None, all_versions=False, limit=20, purpose=None)`

`recognize(memory_id, purpose=None)`

`reconstruct_wire(account, tolerance_pct=5.0, purpose='analytics')`

`remember(content, purpose, confidence=1.0, memory_class='semantic')`

`remember_batch(items, purpose=None)`

`remember_procedure(agent_id, name, instruction_text, purpose=None)`

`resolve(memory_id, purpose=None)`

`resolve_entity_identity(identity, purpose='analytics')`

`run_workflow(name)`

`schedule_job(name)`

`screen_sanctions(name, threshold=None, purpose='compliance_review')`

`search_entities(query, entity_types=None)`

`search_knowledge(query, purpose, top_k=10)`

`search_video_frames(query_id, media_type='VideoFrame', top_k=20, purpose='security_incident')`

`server_health()`

`similar_multimodal(entity_type, entity_id, top_k=10, modality='text', purpose=None)`

`suggest_extensions(prefix)`

`summarise(ids=None, session_id=None, scope=None, contents=None, purpose=None)`

`trace_crypto(address, max_hops=5, min_amount=0, purpose='analytics')`

`trace_hawala(seed, max_hops=5, purpose='analytics')`

`workflow_status(run_id)`