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Stop default openmemory_query from dropping the HTTP session #212

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70a9256
fix: stop default MCP query from dropping HTTP session
vincenzopalazzo Aug 27, 2026
3f87c8a
fix: make Python MCP query timeout and isError actually work
vincenzopalazzo Aug 28, 2026
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173 changes: 138 additions & 35 deletions packages/openmemory-js/src/ai/mcp.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -31,6 +31,55 @@ const sec_enum = z.enum([
const trunc = (val: string, max = 200) =>
val.length <= max ? val : `${val.slice(0, max).trimEnd()}...`;

/** Cap HSG / unbounded graph work so a hung embed or huge scan cannot drop Streamable HTTP. */
const query_timeout_ms = () => {
const n = Number(process.env.OM_MCP_QUERY_TIMEOUT_MS);
return Number.isFinite(n) && n > 0 ? n : 12_000;
};

const with_timeout = async <T>(
p: Promise<T>,
ms: number,
label: string,
): Promise<T> => {
let timer: ReturnType<typeof setTimeout> | undefined;
try {
return await Promise.race([
p,
new Promise<T>((_, reject) => {
timer = setTimeout(
() =>
reject(
new Error(
`${label} timed out after ${ms}ms; try a tighter query or type=factual with fact_pattern`,
),
),
ms,
);
if (typeof (timer as NodeJS.Timeout).unref === "function") {
(timer as NodeJS.Timeout).unref();
}
}),
]);
} finally {
if (timer) clearTimeout(timer);
// Timed-out work may still reject later; swallow so the HTTP
// session is not taken down by an unhandled rejection.
p.catch(() => {});
}
};

const tool_error = (msg: string) => ({
content: [{ type: "text" as const, text: msg }],
isError: true as const,
});

const has_fact_pattern = (fp?: {
subject?: string;
predicate?: string;
object?: string;
}) => Boolean(fp?.subject || fp?.predicate || fp?.object);

const build_mem_snap = (row: mem_row) => ({
id: row.id,
primary_sector: row.primary_sector,
Expand Down Expand Up @@ -140,7 +189,7 @@ export const create_mcp_srv = (tenant?: string) => {
.optional()
.default("contextual")
.describe(
"Query type: 'contextual' for HSG semantic search (default), 'factual' for temporal fact queries, 'unified' for both",
"Query type: 'contextual' for HSG semantic search (default; fails soft on embed/search errors), 'factual' for temporal fact queries (pass fact_pattern or results are capped at k), 'unified' for both",
),
fact_pattern: z
.object({
Expand Down Expand Up @@ -179,7 +228,9 @@ export const create_mcp_srv = (tenant?: string) => {
.min(1)
.max(32)
.default(8)
.describe("Maximum results to return (for HSG queries)"),
.describe(
"Maximum results to return. Applies to HSG queries and to factual queries that omit fact_pattern",
),
sector: sec_enum
.optional()
.describe(
Expand Down Expand Up @@ -221,6 +272,8 @@ export const create_mcp_srv = (tenant?: string) => {
const proj = uid(project_id);
const results: any = { type, query };
const at_date = at ? new Date(at) : new Date();
const top_k = k ?? 8;
const warnings: string[] = [];

if (type === "contextual" || type === "unified") {
const flt =
Expand All @@ -237,44 +290,87 @@ export const create_mcp_srv = (tenant?: string) => {
}
: undefined;

const matches = await hsg_query(query, k ?? 8, flt);
results.contextual = matches.map((m: any) => ({
source: "hsg",
id: m.id,
score: Number(m.score.toFixed(4)),
primary_sector: m.primary_sector,
sectors: m.sectors,
salience: Number(m.salience.toFixed(4)),
last_seen_at: m.last_seen_at,
path: m.path,
content: m.content,
}));
try {
const matches = await with_timeout(
hsg_query(query, top_k, flt),
query_timeout_ms(),
"openmemory_query HSG search",
);
results.contextual = matches.map((m: any) => ({
source: "hsg",
id: m.id,
score: Number(m.score.toFixed(4)),
primary_sector: m.primary_sector,
sectors: m.sectors,
salience: Number(m.salience.toFixed(4)),
last_seen_at: m.last_seen_at,
path: m.path,
content: m.content,
}));
} catch (err: any) {
const msg = err?.message || "HSG contextual search failed";
// Default type is contextual: never let a hung/failed
// embed drop the Streamable HTTP POST. Unified can still
// return facts; pure contextual surfaces a tool error.
if (type === "contextual") {
return tool_error(`openmemory_query failed: ${msg}`);
}
warnings.push(`contextual search failed: ${msg}`);
results.contextual = [];
results.contextual_error = msg;
}
}

if (type === "factual" || type === "unified") {
const facts = await query_facts_at_time({
user_id: u ?? "anonymous",
project_id: proj,
subject: fact_pattern?.subject,
predicate: fact_pattern?.predicate,
object: fact_pattern?.object,
at: at_date,
min_confidence: 0.0,
});

results.factual = facts.map((f: any) => ({
source: "temporal",
id: f.id,
subject: f.subject,
predicate: f.predicate,
object: f.object,
valid_from: f.valid_from,
valid_to: f.valid_to,
confidence: Number(f.confidence.toFixed(4)),
content: `${f.subject} ${f.predicate} ${f.object}`,
}));
const patterned = has_fact_pattern(fact_pattern);
try {
const facts = await with_timeout(
query_facts_at_time({
user_id: u ?? "anonymous",
project_id: proj,
subject: fact_pattern?.subject,
predicate: fact_pattern?.predicate,
object: fact_pattern?.object,
at: at_date,
min_confidence: 0.0,
// Unpatterned dumps can exceed 1MB and stall the
// MCP session; always cap, tighter without a pattern.
limit: patterned ? Math.max(top_k, 32) : top_k,
}),
query_timeout_ms(),
"openmemory_query factual search",
);

results.factual = facts.map((f: any) => ({
source: "temporal",
id: f.id,
subject: f.subject,
predicate: f.predicate,
object: f.object,
valid_from: f.valid_from,
valid_to: f.valid_to,
confidence: Number(f.confidence.toFixed(4)),
content: `${f.subject} ${f.predicate} ${f.object}`,
}));
if (!patterned) {
results.factual_capped = top_k;
warnings.push(
`factual results capped at k=${top_k}; pass fact_pattern to narrow the graph scan`,
);
}
} catch (err: any) {
const msg = err?.message || "temporal fact query failed";
if (type === "factual") {
return tool_error(`openmemory_query failed: ${msg}`);
}
warnings.push(`factual search failed: ${msg}`);
results.factual = [];
results.factual_error = msg;
}
}

if (warnings.length) results.warnings = warnings;

let summ = "";
if (type === "contextual") {
summ = results.contextual.length
Expand Down Expand Up @@ -316,6 +412,13 @@ export const create_mcp_srv = (tenant?: string) => {
}
}

if (warnings.length) {
summ =
warnings.map((w) => `Warning: ${w}`).join("\n") +
"\n\n" +
summ;
}

return {
content: [
{ type: "text", text: summ },
Expand Down
9 changes: 8 additions & 1 deletion packages/openmemory-js/src/temporal_graph/query.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@ export const query_facts_at_time = async (opts: {
object?: string;
at?: Date;
min_confidence?: number;
limit?: number;
}): Promise<TemporalFact[]> => {
const {
user_id,
Expand All @@ -18,6 +19,7 @@ export const query_facts_at_time = async (opts: {
object,
at = new Date(),
min_confidence = 0.1,
limit,
} = opts;
const timestamp = at.getTime();
const conditions: string[] = [];
Expand Down Expand Up @@ -58,12 +60,17 @@ export const query_facts_at_time = async (opts: {
params.push(min_confidence);
}

const sql = `
let sql = `
SELECT id, user_id, project_id, subject, predicate, object, valid_from, valid_to, confidence, last_updated, metadata
FROM temporal_facts
WHERE ${conditions.join(" AND ")}
ORDER BY confidence DESC, valid_from DESC
`;
if (typeof limit === "number" && Number.isFinite(limit)) {
const n = Math.max(1, Math.min(Math.floor(limit), 32));
sql += " LIMIT ?";
params.push(n);
}

const rows = await all_async(sql, params);
return rows.map((row) => ({
Expand Down
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