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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
PATHMARK_STORE_DIRNoDirectory for memory.jsonl. Default: ~/.pathmark/memory
PATHMARK_CODEX_MODELNoOptional Codex model override. Default: unset
PATHMARK_CHAT_COMMANDNoCommand provider: receives a synthesized prompt on stdin and writes an answer on stdout. Default: unset
PATHMARK_OPENAI_MODELNoModel id for OpenAI-compatible synthesis. Default: unset
PATHMARK_CODEX_COMMANDNoCodex provider command. Default: codex
PATHMARK_OPENAI_API_KEYNoOpenAI-compatible API key. Default: unset
PATHMARK_CHAT_TIMEOUT_MSNoSynthesis command timeout. Default: 120000
PATHMARK_OPENAI_BASE_URLNoOpenAI-compatible API base URL. Default: https://api.openai.com/v1
PATHMARK_MAX_SEARCH_RESULTSNoDefault search limit. Default: 12
PATHMARK_SYNTHESIS_PROVIDERNoSynthesis provider: client, command, codex, or openai-compatible. Default: client

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

CapabilityDetails
tools
{
  "listChanged": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_configA

Show the local Pathmark Memory store location and enabled optional features.

rememberA

Save raw searchable evidence. Durable intent should use the approval-gated conclusion workflow.

create_conclusionC

Propose a durable higher-signal conclusion. Approval is required by default before it can be recalled.

search_memoryB

Search saved local memories and conclusions.

get_contextC

Return compact local memory context for a task or question.

recall_memoryB

Transparent recall for any MCP-capable harness. Use this at task start or before answering to show exactly which memories were used.

session_traceA

Show a bounded chronological audit trail for one captured session: prompts, exact injected memory IDs, redacted tool inputs/results, and answers.

rate_recallC

Attach explicit relevance labels to one exact Pathmark recall so audit_memory can report measured precision.

list_conclusionsC

List saved durable conclusions.

list_pending_conclusionsA

List bounded approval-gated conclusion proposals. Pending records are never returned by normal memory search.

approve_conclusionA

Approve one pending conclusion, optionally correcting its text or tags. The transition is atomic and auditable.

reject_conclusionA

Reject one pending conclusion while retaining it in the canonical audit trail and excluding it from recall.

get_memory_snapshotB

Generate a bounded USER/PROJECT/AGENT snapshot from approved canonical conclusions only.

delete_memoryA

Soft-delete a saved memory or conclusion by id.

update_memoryC

Correct an existing memory while preserving its prior versions in local history.

supersede_memoryC

Replace an outdated memory with a linked current record while preserving history.

purge_memoryC

Preview or permanently remove matching records from the canonical store. A backup is created before an applied purge.

consolidate_memoryB

Prepare a bounded unsynthesized evidence batch and, when server synthesis is configured, preview or stage evidence-backed conclusion proposals. Proposals are never auto-approved.

audit_memoryA

Measure capture-to-recall behavior, unused records, recall age, duplicate rate, stale raw hits, and available precision evidence without changing memory.

doctor_memoryA

Report duplicate, deleted, expired, conclusion, invalid-record, and index health counts without changing data.

compact_memoryA

Preview or apply exact deduplication, expired-record removal, retention, and deleted-record purging. Applied runs create a backup.

backup_memoryC

Create a point-in-time copy of the canonical local JSONL store.

export_memoryB

Export a scoped, mergeable JSONL bundle for another Pathmark installation or trusted sync transport.

ask_memoryA

Ask approved conclusions first, then scoped or explicitly requested raw evidence. Returns an answer, exact provenance, and a recallId for feedback.

chatB

Chat with Pathmark using approved conclusions first and only scoped or explicitly requested raw fallback. Returns an answer, provenance, and recallId.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

B3.2/5.0

Scored across 25 tools

Disambiguation2/5

chat and ask_memory are nearly identical in purpose—both answer using approved conclusions first with raw fallback and return provenance plus a recallId—creating clear ambiguity. Additionally, search_memory, get_context, recall_memory, and ask_memory overlap in retrieval behavior, though their descriptions partially clarify output differences. The raw-evidence tools (remember, create_conclusion, consolidate_memory) are more distinct but still require careful reading.

Naming Consistency4/5

Most tools follow a consistent verb_noun snake_case pattern such as create_conclusion, approve_conclusion, delete_memory, and export_memory. A few bare-verb or noun-like names like remember, chat, and session_trace deviate slightly, but the overall convention is recognizable and predictable.

Tool Count3/5

At 25 tools, this sits at the heavy end of the borderline range and feels like more surface than most agents will need. The count is defensible for a full memory lifecycle system covering capture, recall, conclusions, audit, and maintenance, but it risks overwhelming users.

Completeness4/5

The tool set covers the core memory lifecycle well: capture raw evidence, propose and approve conclusions, search and recall, update/delete/supersede, audit, compact, backup, and export. Minor gaps exist—there is no import tool to complement export, and no direct get-by-id retrieval—but agents can work around these via search and export/backup workflows.

Maintenance

ActivityActive
ResponsivenessNo issues